Christian Vang Madsen og Christian NÃ¸rr Jacobsenetd.dtu.dk/.../prod21323243759457_MasterThesis_Collected_Final_1.pdf · Master Thesis Christian Vang Madsen Christian Nørr Jacobsen

Effi ciency Assessment of a Conventional District Energy System and an Alternative CO2 Based Solution

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Christian Vang MadsenChristian Nørr JacobsenMEK-TES-EP-2011-14August 2011

This report has been made as part of the requirements to achieve the M.Sc.Eng degree at the Technical University of Denmark.

This project represents 30 ECTS points for each of the indicated authors.

This project has been carried out in the period: 16th of February – 8th of August 2011

Danish title Effektivitetsanalyse af konventionelt fjernenergisystem og en alternativ CO2-baseret løsning English title Efficiency Assessment of a Conventional District Energy System and an Alternative CO2 Based

Solution

This report was prepared by:

Christian Nørr Jacobsen DTU student number: s052567

and

Christian Vang Madsen DTU student number: s052309

Supervisors

Brian Elmegaard, Head of Section, Lector, DTU Mechanical Engineering Torben Schmidt Ommen, Research Assistant, DTU Mechanical Engineering

External Supervisor

Jørgen Hvid, Senior Consultant, Energy Planning and Production, Rambøll Danmark Karsten Capion, M.Sc.Eng, Energy Planning and Production, Rambøll Danmark

Section of Thermal Energy Systems Department of Mechanical Engineering - DTU MEK Technical University of Denmark Nils Koppels Allé Bygning 403 DK-2800 Kgs. Lyngby Denmark www.tes.mek.dtu.dk Tel: (+45) 4525 4131 Fax: (+45) 4588 4325

Efficiency Assessment of a Conventional District Energy System and an Alternative CO2 Based Solution Page 2/106

1 Abstract This project aims at comparing the efficiency of the existing Danish district heating system with a proposed new energy system, constructed around the idea of creating a network of CO2 throughout the city, which can be used as a refrigerant to supply any thermal energy service within common temperature levels of heating and cooling.

The potential advantages of the propose system includes easy integration of low temperature sources, the ability to deliver all temperature services in a single system and in addition create a synergy effect, where consumers of one thermal energy service would become producers of the other, thereby decreasing the systems overall need for energy input.

Through the project the two energy systems are initially modeled on a unit scale, the results of which is then utilized in the development of a comprehensive system model containing a simplified version of both energy systems.

As a basis for comparison, a case is constructed containing four different consumer types, each with a set of four different energy service demands that are then combined with a projected electricity demand to form the final case. The amount of primary fuel input of both systems, used to cover demand throughout the year is calculated using the simulation model, and finally used in an efficiency comparison.

The results indicate that the existing system uses 8 % less energy than the proposed system when considering the energy system and demand patterns of today. When considering a 2050 scenario, the proposed system still cannot match the efficiency of the existing system, using 3 % additional primary fuel, mainly due to the extensive implementation of large scale heat pumps in the H2O system, enabling the easy integration of excess electricity production from wind turbines into the district heating network.

To determine the impact on the efficiency of the two systems, resulting from a variety of potential changes in the energy system and consumption pattern, a range of sensitivity analysis are carried out. The most interesting results indicate that if more than 35 % of the electricity is produced without heat production then the CO2 system will be more energy efficient. In addition it is determined that the building distribution in the simulated area has a pronounced effect on the results, mainly in connection to the building type’s contribution to the mentioned synergy effect.

Finally a qualitative assessment of the investment and maintenance costs are conducted, which indicates that the proposed system is clearly more expensive in operation than the existing water based solution.

The final recommendations of this report is, that the CO2 system could potentially play a central role in the future energy system if the area of implementation only includes limited CHP production and the building distribution is varied. However before commercial operation can be reached, a number of issues related to safety, control and economics must be further investigated.


2 Table of contents 1 Abstract ................................................................................................................................................. 2

2 Table of contents ................................................................................................................................... 3

3 List of Figures ......................................................................................................................................... 4

4 List of Tables .......................................................................................................................................... 6

5 Contents of Compact Disc (CD) ............................................................................................................. 7

6 Nomenclature ........................................................................................................................................ 8

7 Preface ................................................................................................................................................. 11

8 Introduction ......................................................................................................................................... 12

8.1 Problem statement .......................................................................................................................... 14

9 Reading guide ...................................................................................................................................... 15

10 Energy systems .................................................................................................................................... 16

11 Present H2O based district energy system .......................................................................................... 16

11.1 About the system ............................................................................................................................ 16

11.2 System description .......................................................................................................................... 17

11.3 Superstructure of the existing H2O based energy system ............................................................... 18

12 Proposed CO2 based district energy system ........................................................................................ 24

12.1 CO2 network..................................................................................................................................... 24

12.2 CO2 as network fluid ........................................................................................................................ 26

12.3 Risk assessment ............................................................................................................................... 27

12.4 Pressure drops in distribution pipes ................................................................................................ 33

12.5 Plant side ......................................................................................................................................... 37

12.6 Consumer side ................................................................................................................................. 45

13 Case description .................................................................................................................................. 53

13.1 Basic assumptions ........................................................................................................................... 53

13.2 Consumption ................................................................................................................................... 54

13.3 Final Consumption Pattern .............................................................................................................. 57

14 Available production units ................................................................................................................... 58

15 Introduction to the simulation model ................................................................................................. 65

15.1 Input sheet ....................................................................................................................................... 65

15.2 Results overview .............................................................................................................................. 69

16 Results ................................................................................................................................................. 70

16.1 Base scenario ................................................................................................................................... 70

16.2 Storage in CO2 system ..................................................................................................................... 74


16.3 Distribution between building usage .............................................................................................. 75

16.4 Variations in ground temperature ................................................................................................... 80

16.5 Solar power scenario ....................................................................................................................... 82

16.6 Solar heating .................................................................................................................................... 83

16.7 Geothermal ...................................................................................................................................... 85

16.8 Electricity produced from non-thermal sources ............................................................................. 86

16.9 2050 scenario .................................................................................................................................. 90

17 Overview of system performances and comparisons ......................................................................... 95

18 Economical considerations .................................................................................................................. 96

18.1 Current tax legislations on utilization of waste heat. ...................................................................... 97

19 Conclusion ........................................................................................................................................... 98

20 Future work ....................................................................................................................................... 100

20.1 Different CO2 system layouts ......................................................................................................... 100

20.2 Practical test system ...................................................................................................................... 100

20.3 Optimization of heat pump cycles in CO2 system ......................................................................... 100

20.4 Comprehensive risk assessment .................................................................................................... 100

20.5 Economical investigation of CO2 system ....................................................................................... 100

21 List of references ............................................................................................................................... 102

3 List of Figures Figure 1: Superstructure of the H2O based system ......................................................................................... 18 Figure 2: System diagram of the comfort cooling cycle in the H2O based energy system, numbers representing nodes in the DNA code that can be found in Appendix 3. ......................................................... 20 Figure 3: Cycle illustration of comfort cooling cycle in the water based system, with different condensing temperatures. .................................................................................................................................................. 21 Figure 4: H2O refrigeration system diagram, numbers correspond to nodes in the DNA code found at the end of Appendix 6. .......................................................................................................................................... 22 Figure 5: Cycle illustration of CO2 refrigeration system in supermarket where numbers corresponds to nodes in the DNA code found in the end of Appendix 6. ................................................................................ 23 Figure 6: Superstructure of the proposed CO2 based district energy system ................................................. 24 Figure 7: Water heating with CO2 in a Ts diagram, where the black curve is CO2 and the blue curve is water. ......................................................................................................................................................................... 26 Figure 8: Risk assessment model ..................................................................................................................... 28 Figure 9: Explosive decompression speed ....................................................................................................... 30 Figure 10: Control system with block valves reducing the amount of CO2 leaked to surroundings ............... 31


Figure 11: System diagram showing heat exchanger at plant side to produce vapor CO2 ............................. 38 Figure 12: T,s diagram showing illustration of the plant side heat exchanger cycle ...................................... 38 Figure 13: Vapor production from the sea or the ground dependent on available temperature level. ......... 39 Figure 14: T-s diagram for direct evaporation at hot source temperatures from 8C to 12C .......................... 40 Figure 15: T-s diagram for compressor driven evaporation at hot source temperatures from 8°C to 12°C .. 41 Figure 16: Liquid production from sea or ground dependent on temperature .............................................. 42 Figure 17: Sea water temperatures throughout the year at a depth of 28m near Ven .................................. 43 Figure 18: Illustration of the different liquid production possibilities ............................................................ 44 Figure 19: System diagram of comfort cooling loop with nodes used in DNA code ....................................... 45 Figure 20: T,s diagram of CO2 showing water being cooled from 18°C to 10°C .............................................. 46 Figure 21: System diagram of refrigeration cycle in the CO2 based system ................................................... 47 Figure 22: Cycle representation of the refrigeration cycle in a T, s diagram. ................................................. 48 Figure 23: Refrigeration system schematics for the CO2 system, one with expander and another with valve implemented, the numbers correspond to nodes in the DNA code. .............................................................. 49 Figure 24: Cycle illustration in a T, s diagram of CO2 showing domestic water heating from 8°C to 60°C ..... 50 Figure 25: Cycle illustration in a T, s diagram of CO2 showing domestic water heating from 40°C to 60°C ... 50 Figure 26: System diagram of closed loop cycle with DNA notes ................................................................... 51 Figure 27: T, s diagram of propane showing water being heated from 8°C to 60°C ....................................... 52 Figure 28: T, s diagram of propane showing water being heated from 40°C to 60°C ..................................... 52 Figure 29: Area specific hourly consumption values for a mall ....................................................................... 55 Figure 30: Area specific hourly consumption values for a supermarket ......................................................... 55 Figure 31: Yearly consumption pattern for office buildings ............................................................................ 56 Figure 32: Space heating and hot water consumption per m2 in the residential sector................................. 56 Figure 33: Final consumption pattern for 1,000,000 m2 area in the case model. ........................................... 57 Figure 34: Avedøre CHP plant block 1 production modes .............................................................................. 59 Figure 35: Possible production scenarios with three CHP plants combined ................................................... 60 Figure 36: Thermal production need in excess of CHP production for each system, including storage level in H2O system ...................................................................................................................................................... 71 Figure 37: Hourly coal consumption for each system ..................................................................................... 72 Figure 38: Coal consumption in the CO2 system by implementing storage capacity ...................................... 75 Figure 39: Liquid storage balancing the CO2 system ...................................................................................... 75 Figure 40: Building distribution and yearly coal consumption base scenario ................................................. 76 Figure 41: Distribution between building usage and results – less office and more supermarkets ............... 76 Figure 42: Distribution between building usage and results – less office and more residential and supermarket .................................................................................................................................................... 77 Figure 43: Distribution between building usage and results – less residential and more office, mall and supermarket .................................................................................................................................................... 77 Figure 44: Distribution between building usage and results – Ørestad .......................................................... 78 Figure 45: Remaining thermal demand after balancing measures in 100% supermarket case ...................... 79 Figure 46: Amount of sea based balancing needed at 3⁰C, 8⁰C and 13⁰C ground temperature. ................... 81 Figure 47: CO2 systems coal consumption compared to the H2O systems as function of % solar power implemented ................................................................................................................................................... 83 Figure 48: Impact on coal consumption when introducing solar heating to the energy systems .................. 84


Figure 49: Impact on coal consumption when introducing geothermal to the energy systems .................... 86 Figure 50: Balancing capabilities of the two systems when no CHP heat is available. ................................... 87 Figure 51: Yearly coal consumption for each system, based on the amount of non thermal electricity in the system. ............................................................................................................................................................. 88 Figure 52: Yearly coal consumption for each system with 100% non-thermal electricity production and varying amounts of heat pumps in the H2O system. ....................................................................................... 89 Figure 53: Yearly coal consumption for each system with 100% non-thermal electricity production and heat pumps in the H2O system, while varying the COP. .......................................................................................... 90 Figure 54: Overview of predicted energy system in 2050, [15] ...................................................................... 91 Figure 55: Thermal production need in each system to balance electricity and heat demand ...................... 93 Figure 56: Overall biomass consumption in CO2 system and H2O storage system ......................................... 94

4 List of Tables Table 1: Pressure, supply-and return temperature of district heating network ............................................. 19 Table 2: Results of the comfort cooling cycle in the water based district energy system. ............................. 20 Table 3: COP calculation for different ambient temperatures ........................................................................ 22 Table 4: Table of relevant properties of ammonia and CO2 ............................................................................ 27 Table 5: Concentration of CO2 in the air, exposure time and effect on humans ............................................ 29 Table 6: Allowed pressure drops before phase change begins at isenthalpic conditions. ............................. 33 Table 7: Pressure drops in district heating pipes of water and vapor CO2 ...................................................... 34 Table 8: Pressure drops in the CO2 vapor pipeline using different pipe diameters ........................................ 35 Table 9: Pressure drops in the liquid CO2 pipeline using different pipe diameters ........................................ 36 Table 10: CO2 evaporating heat exchanger results ......................................................................................... 38 Table 11: Efficiencies in central vapor production based on water from the sea........................................... 40 Table 12: Temperature steps used in simulations .......................................................................................... 42 Table 13: Efficiencies in central liquid production based on varying temperatures of water from the sea ... 43 Table 14: Cooling water use at Kgs. Nytorv district cooling plant in full operation ........................................ 44 Table 15: Results of the CC cycle ..................................................................................................................... 46 Table 16: Final refrigeration cycle results ....................................................................................................... 47 Table 17: Final cycle results for the OLDHW unit ............................................................................................ 49 Table 18: Results of the closed loop cycle ....................................................................................................... 51 Table 19: Distribution of building area in Copenhagen ................................................................................... 53 Table 20: Energy services needed in the included consumers ........................................................................ 53 Table 21: Fuel distribution for electricity production Eastern Denmark 2010 ................................................ 58 Table 22: Full load specifications for Avedøre CHP plant block 1. .................................................................. 59 Table 23: Operational limits of a system including 3 CHP plants, one with a maximum heat production of 5000 kJ/s and two with a maximum heat production of 10000 kJ/s .............................................................. 60 Table 24: Values used for the calculation of storage size ............................................................................... 61 Table 25: Total yearly coal consumption of each system ................................................................................ 72


Table 26: Calculation of fuel input needed for the CO2 system to produce the same output as the H2O system. ............................................................................................................................................................. 73 Table 27: Coal spot market prices in 2009 ...................................................................................................... 73 Table 28: Operation cost of both energy systems........................................................................................... 74 Table 29: Yearly CO2 emissions from operating both energy systems ........................................................... 74 Table 30: Extreme cases with 100% building distribution of each consumer type ......................................... 79 Table 31: State points used for sensitivity analysis of the ground temperatures influence on systems performance. ................................................................................................................................................... 80 Table 32: COP and specific CO2 usage values for the CO2 network at different average ground temperatures. ......................................................................................................................................................................... 80 Table 33: CO2 enthalpy values for the two state points at different ground temperatures. .......................... 81 Table 34: Development in the two types of electricity consumption in the CO2 system for different ground temperatures. .................................................................................................................................................. 82 Table 35: Coal consumption values for different ground temperatures. ....................................................... 82 Table 36: Area of solar panels in Denmark – existing and projected .............................................................. 84 Table 37: Yearly coal consumption for each system, based on the amount of non thermal electricity in the system .............................................................................................................................................................. 88 Table 38: Yearly coal consumption for each system with 100% non-thermal electricity production and varying amounts of heat pumps in the H2O system. ....................................................................................... 89 Table 39: Yearly coal consumption for each system with 100% non-thermal electricity production and heat pumps in the H2O system, while varying the COP ........................................................................................... 90 Table 40: Electricity and heat production composition and inputs to simulation model ............................... 92 Table 41: Yearly biomass consumption in each system .................................................................................. 94 Table 42: Summarized results from all the simulated scenarios and sensitivity analysis. .............................. 95 Table 43: Comparison of investment costs ..................................................................................................... 96

5 Contents of Compact Disc (CD) The enclosed CD can be found on the last page of the appendix, and contains the following items:

• Excel files • DNA files • EES files • Utilized references • Digital representation of the report and appendix.


6 Nomenclature CC Comfort Cooling CCS Carbon Capture Storage CFC ChloroFluoroCarbon CHP Combined Heat and Power CLDHW Closed Loop Domestic Hot Water COP Coefficient of Performance DHW Domestic Hot Water DKK Danish Currency DN Diametre Nominal DNA Dynamic Network Analysis DNV Det Norske Veritas DTU –MEK Department of Mechanical Engineering, Technical University of Denmark EES Engineering Equation Solver EU European Union GWP Global Warming Potential HCFC HydroChloroFluoroCarbon HFC HydroFluoroCarbon HP High Pressure LHV Lower Heating Value LP Low Pressure HVap Latent heat of vaporization ODP Ozone Depletion Potential OLDHW Open Loop Domestic Hot Water PP Power Production REFRI Refrigeration SH Space Heating Chemical scripts CO2 Carbon dioxide H2CO3 Carbonic Acid H2O Water Greek Symbols η Efficiency Δ Difference or ratio ρ Density Φ Distribution Superscripts [ ]̇ Time dependent rate Subscripts air Ambient air amb Ambient bar Pressure given in bar


brine Ethylene Glycol 30% comp Compressor cond Condenser crit Critical evap Evaporator exp Expander fan Referring to fan FBM Full Backpressure FCM Full Condense Mode in Inlet state inner Referring to inner diameter is Isentropic liq CO2 liquid max Maximum min Minimum molar Referring to molar mass out Outlet state prop Propane return Return temperature in district heating network sat Saturating simul Referring to simulated results step Referring to temperature steps storage Storage sub Subcooling suc Referring to suction temperature sup Superheat supply Supply temperature in district heating network sw Sea water tot Total vap CO2 vapor w Water Mathematical Symbols A Area [m2] Cp Specific heat capacity [kJ/(kg·K)] Cv Volumetric heat capacity [kJ/(m3·K)] h Enthalpy [kg/kJ] k Roughness factor [m] L Length [m] M Mass [kg] N/n Number [-] P Pressure [bar] p head loss [m H2O] (meter water column) Pratio ratio between Pcond and Pevap [-]


�̇� Thermal energy transfer rate [kW] T Temperature [°C] v Velocity [m/s] V Volume [m3] W Work (Mechanical) [kW]


7 Preface This master thesis is prepared by Christian Nørr Jacobsen and Christian Vang Madsen, as part of the requirement for achieving the degree M.Sc. Eng from the Technical University of Denmark. Both authors are studying the M.Sc. Eng Sustainable Energy with focus on thermal energy, which is offered by Risoe DTU, the National Laboratory for Sustainable Energy.

This thesis has been carried out in collaboration with Section of Thermal Energy Systems, part of the Department of Mechanical Engineering at the Technical University of Denmark and Rambøll Denmark.

We would like to thank to number of people, with a special thanks to our supervisors, who has assisted us throughout this project as it has been a great help in preparing this thesis.

Head supervisor Brian Elmegaard who suggested the project idea and has offered his time and guidance, which has been very valuable.

Torben Schmidt Ommen, for answering questions and provided support whenever needed.

Jørgen Hvid and Karsten Capion, for providing information and knowledge about the district heating system. Additionally, Jørgen and Karsten has always offered their time and guidance to answer question and provided their guidance.

This assessment relies heavily on measurement data and these have been provided from several persons whom we would like to thanks.

Jesper Thorsgaard Larsen, Technical Department at Dansk Supermarket, for answering questions regarding the supermarket refrigeration system and providing supermarket consumption data.

Lars Gissel, DAB energy group, for providing heat consumption data from two building complexes.

Jesper Mariegaard, Vandvagt Vandudsigten DHI, for providing sea water temperatures from Ven.

Simon Furbo, Department of Civil Engineering Technical University of Denmark, for providing measured weather data from a reference year.


8 Introduction The Danish energy system is the most efficient in Europe [1], partly because of the extensive use of low temperature reject heat from power production in district heating networks. This system is constructed around the pretense that electricity is produced by means of burning fuel to drive generators, ensuring continuous availability of low temperature reject heat.

During the latter years a range of changes in the composition of the energy system is challenging this concept, making it important to consider how the district heating system will work in collaboration with a future energy system, which is very different from the one that started the movement towards district heating.

The Danish government’s long term goal is that Denmark is to become 100% independent of fossil fuels [2], a development that will be initiated by almost a doubling of the amount of renewable energy from 17% in 2005 to 30% in 2025. This will partly be accomplished by increasing the amount of wind power from 18.3% of the total electricity production in 2009 [3] to 50% by 2025 [4]. This indicates that the amount of electricity production from Combined Heat and Power (CHP) plants will decrease accordingly, leading to situations where power consumption is satisfied without the necessary heat demand being met.

These situations are likely to occur more often in the future, as the renewable energy sector is further developed, and a variety of solutions are presently being discussed, including large central solar heat implementation, the use of large electric heating elements in the district heating plants or the implementation of large heat pumps to efficiently turn surplus electricity into heat. All of these possibilities are centered around the idea that additional heat, preferably based on renewable sources, must be supplied to the district heating systems in times with low to no power production in CHP plants.

At the same time the European Union has agreed that all new buildings must be nearly zero-energy buildings by 31. December 2020 [5], which in a country as Denmark, where ambient temperatures are below room temperatures for most of the year, leads to increased insulation needs. The resulting decrease in heat consumption could to some degree alleviate the problems with ensuring an adequate heat supply for the district heating network, but also raises other topics such as the resulting potential for increased cooling demand in summer time. A situation which is further supported by the growing amount of electronics inside buildings and the present and expected temperature increases due to climate change [6][7].

It seems inadequate to focus the energy system solely on heat supply when that is expected to decrease while cooling demand is expected to increase in the future. The Danish utility companies realize this and in an effort to address this issue Copenhagen’s first district cooling central was opened in 2010 [8]. The system is a modified version of the district heating system, leading to a range of limitations to be considered, firstly the use of water as a medium limits the supply temperature and thereby utilization possibilities to temperatures above 0⁰C, secondly the relatively low temperature difference between supply and return temperatures leads to fairly large amounts of water, and therefore large pipe diameters, being needed to remove a certain amount of energy from a given site, making this a less than perfect solution.


An optimal future energy system should be capable of delivering both heating and cooling and be versatile in regard to both output temperatures and available energy inputs. Presently the most versatile energy carrier is electricity, which is regarded as the natural basis for the energy system of the future [9]. The most efficient method of converting electricity to thermal energy is using heat pumps, where a part of the delivered energy is obtained from a thermal source and the electricity merely drives the energy transfer.

The current implementation of this idea is decentral heat pumps for heat production and decentral heat pumps for cooling demands, the only difference being the direction of energy transfer. During heat production energy is obtained from the surrounding and moved to the desired location at a higher temperature. During the production of cooling, energy is obtained from the desired cold spot and released into the surroundings. Thereby, using electricity in combination with heat pumps it is possible to deliver all necessary thermal demands in an energy efficient way, while remaining relatively independent of the available primary energy sources.

It is obvious that these two production methods could be combined to deliver both heating and cooling simply by utilizing both sides of the heat pump, which is an area that has seen extensive research in the last couple of years, especially with regard to supermarkets that use large amount of both heating and cooling [10]. Temperature demands in the rest of the industry are not necessarily as well balanced, thus this kind of co-generation is not directly feasible. A situation much similar to the one in Denmark before it was decided to begin piping power plant cooling water throughout Copenhagen to supply heat for the city.

The same approach could solve the problem of balancing the thermal demands of an area. By creating a refrigerant network for heat pumps, the refrigeration system of an office building or supermarket could be used to produce heating for domestic purposes at the other end of town, thereby minimizing the amount of energy that is simply released into the ambient environment and thereby lost. A district energy system based on this idea would present a range of beneficial effects when compared to the existing water based system, and could potentially prove more efficient.

In this project such an energy system is proposed, inspired by [11], where a CO2 based district energy system supplies decentral heat pumps with pressurized refrigerant, which can be utilized to produce either heating or cooling at all commonly used temperature levels. The system consists of two network pipelines in which CO2 is kept close to a saturation pressure corresponding to 8°C, meaning 45 bar in the liquid phase pipe and 40 bar in the vapor phase pipe. The phase change energy can then be utilized in heat pumps by evaporating liquid CO2 for cooling purposes and condensing vapor CO2 for heating purposes. CO2 are in each process evaporated or condensed from one pipe to the other, in effect creating a synergy effect between heating and cooling demands. Thereby what is presently seen only as energy consumers will, to some extent, become energy producers by making heating or cooling available to other consumers. This leads to less energy waste, and enables a distributed system balancing effect where the users themselves help to balance the system, thus reducing demand for central balancing measures.

Operating the CO2 network at an annual average ground temperature of 8°C [12], is advantageous in regards to two issues. Firstly this limits the heat transfer to and from the surrounding soil, reducing the thermal energy loss in the system and secondly it enables utilization of all excess temperature sources along the network for balancing measures. Heat sources such as ambient air, solar heating, geothermal, industrial waste heat, excess heat from CHP plants and even the sea can be easily implemented and used to


evaporate CO2 to vapor and thereby produce heat for the network. In the same respect, cooling sources such as ambient air, ground water and the sea can be utilized to condense CO2 to liquid and produce available cooling.

8.1 Problem statement The aim of this project is to perform a preliminary assessment of a novel type of district energy system based on pressurized CO2 as working fluid, which is done in an attempt to mitigate drawbacks and limitations of the present H2O based district energy system. The proposed and the present energy system will be compared in a modeled case study, which seek to represent real life conditions by replicating a Copenhagen city area including actual consumption and production data.

As part of the assessment the composition of the CO2 network and performance of each type of cycle in regards to the Danish energy system conditions will be determined. Performance data will serve as inputs to a simulation model along with consumption and production data in order to obtain a comparison of the energy systems based on the amount of energy needed for the system to supply the required energy services.

Sensitivity analysis of the both energy systems will be carried out by varying relevant parameters on the case system, and additionally introduce different energy scenarios in order to identify system impacts. Results of the system comparisons, sensitivity analysis and scenarios serves as an identification of boundaries to clarify under what conditions the CO2 system could be preferable. This also includes a mapping of the opportunities and barriers of having a CO2 based district energy system instead of H2O based one.


9 Reading guide A short description of the composition of the report is presented to provide an overview of the report structure, briefly outlining the steps taken to obtain the final results.

The report starts with a brief description of the thermal parts of the present H2O based energy system, where the district heating system and decentral cooling systems supplying the thermal energy services are presented along with simulated cycle performance results and cycle illustrations. Next a more comprehensive description of the proposed CO2 energy system and each type of heat pump are presented, which includes system diagrams, cycle performance results and cycle illustrations. Additionally, critical issues related to pressure drops in the pipelines and a risk assessment of the system is also presented.

Afterwards a number of assumptions are stated that form the basis for a case scenario, which consists of a set of hourly consumption patterns for four different thermal energy services and electricity through an entire year. This will later form the basis for the comparison between the energy systems, by describing the demands that each system must satisfy.

Next the available production units, primarily Avedøre CHP plant block 1, responsible for covering the heat and electricity demand are explained along with the relevant assumptions about their limitations and possibilities.

A brief explanation of part of the Microsoft Excel simulation model is then given as an introduction before the results of the base scenario comparison is supplied. The model contains all consumption and production data, and is used to simulate system behavior and performance from which results can be derived. Afterwards a range of different scenarios are simulated to clarify how a variety of different changes influence the results of the two systems, indicating under which circumstances each of the systems would be preferable.

Finally the report sums up the obtained results and attempts to conclude whether or not the proposed CO2

system might be worth considering further.


10 Energy systems In the following sections the two energy systems, the present H2O based system and the proposed CO2 system, will be presented. Initially a description of the systems will be given to ensure an understanding of how they are composed with regards to production and delivery of thermal energy services. Both systems only cover the electricity and thermal energy sectors, thus excluding the transportation and industrial ones.

The systems are composed of different cycles, most predominantly in the CO2 system, and each of these will be briefly explained along with relevant assumptions and operating conditions. Based on this, calculations of system performances and mass flow rates in the cycles are carried out in a simulation tool called Dynamic Network Analysis (DNA). See Appendix 1. These results will later serve as inputs to a final simulation model that is able to simulate the entire CO2 and H2O system. Only the most important aspects of each cycle will be presented in the report, while a more elaborate description including system components can be found in the referred appendices.

11 Present H2O based district energy system In this section the appropriate considerations, assumptions and calculations of the existing H2O based system will be described, starting with a brief explanation of the most problematic issues to be considered, and afterwards a description of how the system actually functions.

11.1 About the system As mentioned, the energy system in Denmark is the best in Europe with regard to energy efficiency [1], and with good reason as Denmark since the oil crisis has been focused on optimizing the energy sector [13]. This has led to the advanced and very extensive district heating network, which supplies most of the population in densely populated areas with domestic hot water and space heating. There is however a number of problematic issues related to the current system and these issues are some of the key motivators behind proposing another possible district energy system, as this novel system aims to address these points. These issues will be explained in the following sections.

11.1.1 Heat production from boilers As mentioned in the introduction, the present system is constructed around the pretense that electricity is produced by means of burning fuel to drive generators, thereby ensuring continuous availability of low temperature reject heat used for district heating. In recent years the extensive development of the renewable energy sector, which does not supply reject heat, mainly wind power, has lead to situations where the needed electricity production has not delivered the required amount of heat for the district heating networks, thus forcing the utilities to run boilers solely for heat production. These situations are likely to occur far more often in the future, as the renewable energy sector is further developed, increasing the demand for balancing measures. According to energy plans [14][15][9], boilers and to a limited extent also large electrical heating elements will play a key role in balancing the increasing share of fluctuating production. Implementation of large heat pumps to more efficiently turn surplus electricity into heat is also an option under development, but that is still in an early stage of development.


11.1.2 Energy loss from pipes The district heating system today is based on water as an energy carrier, and this have its benefits but also its drawbacks. Using water as an energy carrier means that the supply temperature from the production facility needs to be between 75-120°C [16], depending on the season, as temperatures has to be high enough to ensure adequate supply temperatures at the farthest end of the distribution network. This is a disadvantage because the higher the CHP output temperature is, the higher the temperature difference between the water and the soil surrounding the pipelines become, which leads to increased heat losses throughout the system. The problem is logically most dominant in areas where consumers are located far away from each other and the central heating plant, resulting in varying losses in the range of 7 % - 30 % [17].

11.1.3 High temperature requirements Another drawback is that low temperature heat sources such as solar heating, geothermal or waste heat from the industry, often have a too low temperatures to be directly implemented in the district heating supply line. Solar heating has a very high potential, and is able to supply high enough temperatures during the summer, but have too low temperature during most of the spring and fall and almost never during winter [18], which eventually leads to fewer utilization hours impacting the economy adversely. Geothermal is a stable heat source, but has the drawback with regard to the current district heating system that the boreholes have to be several kilometers deep in order to reach feasible temperatures to be used directly for district heating[19]. Additionally the temperature requirement limits the number of suitable locations, which is a barrier for large scale implementation. The temperature of waste heat from the industry can vary a lot, and each case must be considered individually in relation to available temperature, amount of heat available, and if it is economically feasible in relation to investments and the energy tax laws. Presently these sources are only sparingly implemented, and often the temperature requires boosting using heat pumps to allow for appropriate output temperatures for the network.

11.2 System description Only a brief description of the plant and consumer side of the district heating system is presented, as this is assumed to be familiar knowledge to the reader. A more thorough description of the refrigeration (REFRI) and Comfort Cooling (CC) systems are included as assumptions and choices of components influence the resulting coefficient of performance (COP), see Appendix 2, which will play a central part in the final simulation model.


11.3 Superstructure of the existing H2O based energy system An illustration of the superstructure of the H2O based energy system is presented in Figure 1 below.

Figure 1: Superstructure of the H2O based system

11.3.1 Plant side In the following section the production side of the present H2O based district energy system will be briefly explained.

11.3.1.1 Heating mode Heat can be produced either centrally or decentrally, which mainly depend on the population density in the area and the district heating plan. Decentralized heating is typically produced by oil- or natural gas boilers supplying it either as Domestic Hot Water (DHW) or Space Heating (SH) through radiators or floor heating. In the current report, only centrally produced heat is included since the investigations focus on a city area modeled after Copenhagen where 98% of the city is supplied with district heating [14]. The production of district heating in Denmark is based on a variety of production types, the primary one being CHP plants running on biomass, coal, fuel oil, gas or waste, but in addition, sources such as solar heating, geothermal and heat pumps also contribute to a varying degree. In this report, only the coal powered Avedøre CHP plant supported by boilers is included in the case base scenario, but other heat sources adding to district heating production will be looked into in the sensitivity analysis in sections 16.6 and 16.7.

District heating provides the energy services DHW and SH by producing heat centrally as a byproduct from electricity production (From CHP) and circulates hot water from the plant through transmission- and distribution pipes to heat centrals and then back to the plant again. Hot district heating water leaves the plant at high temperatures, the highest during winter and lowest during summer both because of demand and to compensate for increased heat losses in the pipelines. Typical temperatures in the district heating network can be seen in Table 1 [16], but both pressures and temperatures are highly dependent on each individual network.


Transmission Unit Distribution Unit Pbar 25 Bar Pbar 6.5-10 Bar Tsupply 95-115 °C Tsupply 80-105 °C Treturn 45-60 °C Treturn 40-50 °C

Table 1: Pressure, supply-and return temperature of district heating network

Temperature levels of supply and return water are not included in this project, since the efficiency of the CHP plant is based on supplying the adequate temperatures. Instead the actual amount of energy delivered to consumers will be utilized in the simulations. More details about operation of Avedøre CHP plant block 1 is covered in section 14.1.1.

11.3.2 Distribution network Hot water produced at the plant is let into the supply transmission pipe, which has a very large diameter near the plant in order to transport large volumes. The transmission supply line is then split into smaller distribution networks, and from these branch pipes supplies heat centrals. Return lines are placed together with supply lines and follow the same network pattern.

Heat loss from the pipelines to the surroundings is inevitable due to the high temperature difference, but the percentage of district heating lost to the surroundings through the pipelines varies a lot. According to [17] and as mentioned in the introduction the heat losses amount to 7% – 30% of the district heating delivered, mainly dependent on the density of consumers in the network. In the base scenario dealt with later in this report a heat loss of 7% is assumed as the consumer density is high in Copenhagen. This percentage includes all heat losses in pipelines and in heat exchangers at the plant side. Pressure losses occur in the district heating pipelines and the effect of this will be treated in section 12.4.

11.3.3 Consumers side In the following section the consumer side of the present district energy system will be briefly explained.

11.3.3.1 Heating mode

The heat from the production plant is transferred through heat exchangers in district heating centrals to circulation water, to and from clusters of consumers who are connected to the centrals. Heated water is used for DHW in the taps and for SH which flows through radiators or floor heating, transferring heat by radiation to the room. The water is then circulated back to get reheated and the used volume of hot tap water are replaced by cold tap water in the circulation loop.

11.3.3.2 Comfort Cooling – CC The following sections shortly present the main aspects of the comfort cooling cycle, but a more elaborate description including the chosen components can be found in Appendix 3.

Comfort cooling is becoming increasingly widespread in Denmark, mainly in office buildings, malls, supermarkets and other public places. Some residential houses also have comfort cooling installed, but this is not common, thus this will not be including in the initial systems. Considerations regarding a possible increase in demand in the future are however covered in a discussion in section Error! Reference source not found..


Comfort cooling can be provided either by central production through a district cooling network or produced decentral by individual systems. Though Copenhagen has a district cooling central near Kongens Nytorv supplying large consumers at the city center [8], it is chosen to assume that comfort cooling will be provided by decentral production as this is the most common practice in the present energy system.

11.3.3.2.1 System diagram A system diagram of the comfort cooling cycle with an intermediate loop between condenser and dry cooler can be seen in Figure 2 below.

Figure 2: System diagram of the comfort cooling cycle in the H2O based energy system, numbers representing nodes in the DNA code that can be found in Appendix 3.

A simple air cooled condenser were originally chosen as condenser type, but calculations made by TT Coil A/S showed a surface area and pressure loss on the refrigerant side that was too high. See Appendix 4. Focus was then shifted to a dry cooler which requires an intermediate loop with brine between the outside air cooler and the refrigerant condenser. A brine was chosen instead of water as a medium to avoid problems with freezing as the dry cooler is situated outside where temperatures might reach below 0°C.

11.3.3.2.2 Results To calculate the COP of the cycle several assumptions has been made. The temperature lift of the ambient air will be 7.5K regardless of ambient temperature, even though it in practice will be very hard to control this exactly. Additionally, power consumption of the fans in the dry cooler are also assumed constant. Calculations have been made down to outdoor temperatures of -20°C, as comfort cooling is needed even during the winter in both office buildings and malls. Graphs showing the consumption pattern of malls and office buildings are illustrated in section 0 and 13.2.3 respectively, and the data used to make the graphs can be found in excel files “mall consumption” and “office building consumption”. Performance results of the comfort cooling cycle can be seen below:

Tamb step Tcond �̇� Wfan Wtot COP �̇�R410A �̇�air

[C] [°C] [kJ/s] [kW] [kW] [-] [kg/s] [kg/s] -20 10 80 4.51 12.21 6.55 0.36 11.58

-17.5 10 80 4.51 12.21 6.55 0.36 11.58 -12.5 10 80 4.51 12.21 6.55 0.36 11.58 -7.5 10 80 4.51 12.21 6.55 0.36 11.58 -2.5 12.5 80 4.51 12.95 6.18 0.37 11.68 2.5 17.5 80 4.51 14.55 5.50 0.38 11.89 7.5 22.5 80 4.51 16.38 4.88 0.4 12.13

12.5 27.5 80 4.51 18.52 4.32 0.41 12.41 17.5 32.5 80 4.51 21.09 3.79 0.43 12.75 22.5 37.5 80 4.51 24.26 3.30 0.46 13.17 27.5 42.5 80 4.51 28.26 2.83 0.48 13.69 30 45 80 4.51 30.68 2.61 0.5 14.01

Table 2: Results of the comfort cooling cycle in the water based district energy system.


11.3.3.2.3 Cycle illustration In Figure 3 the comfort cooling cycle in a log ph diagram of R410A is shown with different condensing temperatures. This log ph-diagram and all of the following of this type has been obtained from the software Coolpack, which can be downloaded from [20].

Figure 3: Cycle illustration of comfort cooling cycle in the water based system, with different condensing temperatures.

11.3.3.3 H2O system Refrigeration The following sections shortly present the main aspects, but a more elaborate description including cycle components can be found in Appendix 6.

11.3.3.3.1 Purpose In the current system, the standard means of obtaining refrigeration is using a normal compression cycle with an outside air condenser. In the constructed scenario, the only area utilizing low temperature refrigeration are supermarkets, therefore the refrigeration system simulated will be constructed based on the demands of these systems.

11.3.3.3.2 System diagram Because the needed temperatures are very low, -15°C for cooling and -35°C for freezing [21][22], a brine is avoided and instead the refrigerant is sent directly to the refrigerated areas, leading to a situation where the pressurized refrigerant is transported throughout areas where the customers are shopping. This raises demands that the refrigerant must be both nontoxic and inflammable, which, combined with restrictions on HFCs, leads to R744 (CO2) being the current industry standard in supermarket refrigeration systems.

There are many possible ways to construct a supermarket refrigeration system, but to ensure a fair comparison the same system construction is assumed to be used in both the CO2 and H2O system, with the obvious exception that the two supply lines connected to the outside air condenser/gas cooler, dependent on ambient temperatures, in the H2O system, is instead connected to the proposed CO2 network.


Figure 4: H2O refrigeration system diagram, numbers correspond to nodes in the DNA code found at the end of Appendix 6.

When determining the performance of the cycle, the distribution between the two temperature levels is important, because the lowest temperature affects the efficiency negatively. A distribution of 60 kW cooling at -15⁰C and 20 kW freezing at -35⁰C has been chosen for both the H2O system and CO2 system[21][22].

11.3.3.3.3 Results Based on the mentioned considerations, the refrigeration system has been modeled in DNA, resulting in the following values for a range of outside temperatures.

Tout step Condensing or Transcritical �̇�air Pcomp Wtot COP

[C] [kg/s] [bar] [kW] -20 Condensing 5.86 30.65 10.28 7.78

-17.5 Condensing 5.96 32.79 11.81 6.77 -12.5 Condensing 6.08 35.03 13.64 5.87 -7.5 Condensing 6.31 39.87 17.09 4.68 -2.5 Condensing 6.55 45.19 20.87 3.83 2.5 Condensing 6.83 51.02 25.04 3.19 7.5 Condensing 7.03 54.15 28.09 2.85

12.5 Condensing 7.37 60.85 33.33 2.40 17.5 Transcritical 7.96 75.177 42.3 1.89 22.5 Transcritical 8.22 75.177 46.18 1.73 27.5 Transcritical 8.7 75.177 53.54 1.49 30 Transcritical 9.09 85.177 59.41 1.35

Table 3: COP calculation for different ambient temperatures

The determined COP values are used in the simulation model, see Excel file “Simulation model” to calculate the corresponding hourly electricity consumption used for refrigeration in the existing H2O system.

11.3.3.3.4 Cycle Illustration In Figure 5 the supermarket refrigeration cycle with three different ambient temperatures, -20°C, 12.5°C and 30°C, are plotted in a T-s diagram. This T-s diagram and all of the following of this type has been obtained from the software Coolpack, which can be downloaded from [20].


Figure 5: Cycle illustration of CO2 refrigeration system in supermarket where numbers corresponds to nodes in the DNA code found in the end of Appendix 6.


12 Proposed CO2 based district energy system Based on article [11], a novel district energy system is proposed which utilizes CO2 as an energy carrier able to function as both heat source and heat sink for decentral thermal production. An illustration of superstructure of the proposed system can be seen in Figure 6.

Figure 6: Superstructure of the proposed CO2 based district energy system

From the functional point of view, the proposed system requires a variety of different changes to be made, both at plant side and consumer side. In the following, the function of the network and the different cycles will be explained along with the appropriate considerations, assumptions and calculations.

12.1 CO2 network The CO2 network itself is the heart of the proposed system and consist of two separate pipelines containing pressurized CO2, where one contains liquid and the other vapor. The liquid line has a pressure of 45 bars whereas the vapor line has 40 bars, which results in saturation temperatures of 10⁰C and 5.3⁰C respectively, placing the average ground temperature in Denmark of 8°C [12] between them, thereby minimizing heat loss to the surrounding soil. Having this network temperature means that the liquid line has 2.7K subcooling and the vapor line has 2K superheat, see Appendix 8, to avoid small pressure drops or temperature changes causing phase change and as a consequence decreasing system performance. The effect of pressure drops and changes in temperature in the surrounding soil is investigated in section 12.4 and 16.3 respectively.


Energy services are provided differently when compared to the present system, as CO2 serves as a heat source (vapor line) and a heat sink (liquid line) for decentral machinery installed at the consumers. The machinery is able to produce heating (open and closed loop) and cooling (comfort cooling and refrigeration) by utilizing the latent heat in the CO2. Since both the liquid and vapor is kept close to the saturation pressure, phase change can easily occur and can deliver or obtain close to 214kJ/kg CO2. The CO2 network enables a very interesting synergy effect, where consumers, presently seen only as energy consumers, to some degree will become energy producers of either cooling or heating. I.e. when a consumer evaporates CO2 liquid for cooling purposes, vapor is returned to the network thereby becoming available to other consumers as a heat source. The same is the case when a consumer condenses CO2 vapor for heating purposes, then liquid is returned to the network, where it becomes available as a heat sink for other consumers. Due to this energy exchange between consumers, the network creates a balance to some extent, and thereby limits the energy input needed to condense or evaporate CO2 at the plant side in order to fulfill the demands of the consumers. This could potentially contribute to high energy savings in periods where the demand for cooling and heating are similar in size. Theoretically the network could balance itself out thermally, meaning that no energy is supplied centrally, except for the electricity for pumps and compressors.

12.1.1 Inclusion of low temperature heat sources One of the major advantages of the proposed system is the easy integration of various low energy temperature sources. Even temperatures below the network temperature can be used to produce CO2 vapor for the system, meaning that there will never be a shortage of thermal energy. It is however clear that energy sources above the pipeline temperature is far more desirable, since no energy would then be needed to compress the vapor back to system level. Even with this in mind, there are still a large number of different sources to choose from; even in full condensing mode a power plant produces excess heat at approximately 30⁰C which needs to be cooled to 10⁰C, cheap solar panels are far more efficient when only low temperatures are needed, in Frederikshavn the sewage water between 6⁰C and 18⁰C are already being used as a heat source for a heat pump supplying the district heating system, [23] and geothermal energy is much more easily obtained when only low temperatures are needed.

12.1.2 Ability to supply all thermal energy services within one system Due to the use of water as an energy carrier, the existing district energy system is only able to provide heating through district heating, and cooling purposes are produced by separate systems not connected to the other part of the thermal system.

The proposed system is able to function as a heat source and a heat sink making it possible to utilized the CO2 to produce energy services between -70°C and 150°C depending on the decentral machinery. A major benefit of the CO2 system, is that it needs only two pipelines, which does not need to have large diameters due to low mass flow rates, and thereby do not obtain more space in the underground infrastructure than the existing system. This statement is supported by findings in section 12.4. Additionally every component providing a thermal energy service is connected into one network, making it easier to balance the system centrally and exploit the synergy effect mentioned above.


12.2 CO2 as network fluid In this section it will be explained why CO2 has been chosen as the network fluid, and how it has excellent properties to be a transport and working fluid for compressors in a district energy system.

Danish laws and regulations states that all CloroFluoroCarbon (CFC) and HydroCloroFluoroCarbon (HCFC) refrigerants are banned due to their Global Warming Potential (GWP) and Ozone Depletion Potential (ODP) [24]. Another type of refrigerants, HydroFluroCarbons (HFC), are only restricted in heat pumps, air conditioners and refrigeration plants with a refrigerant content of up to 10 kg, [25] meaning that it can only be used to a limited extend. With regard to the Danish laws, only natural refrigerants can be considered as possible network fluids due to the large quantities needed.

CO2 is a natural refrigerant which is environmental friendly, have no ODP, and a GWP of 1. Additionally it has low toxicity, is non flammable, is chemical inactive and have very high availability [26]. CO2 has the property of having a critical point at 31.1°C and is transcritical at temperatures above this point. Working in the transcritical region normally makes a heat pump cycle less efficient as it requires more compressor work and no condensation takes place. However, the unique temperature glide of CO2 in the transcritical region, makes it well suited for water heating, as a very small pinch can be achieved. This is visualized in Figure 7, where water is heated from 8°C to 60°C by transcritical CO2 in a gas cooler.

Figure 7: Water heating with CO2 in a Ts diagram, where the black curve is CO2 and the blue curve is water.

Another very good and essential property of CO2 is that it has a gas density very close to the liquid density at the CO2 network temperature, [27]. This makes the system very tolerant to small pressure drops and temperature changes which can partly vaporize or condense CO2 in the pipelines. The high vapor density also leads to high volumetric heat capacity, which makes CO2 an excellent energy carrier that can absorb and release heat effectively. CO2 offers good possibilities as a transport fluid and as working fluid in heat pump cycles, especially for water heating. The only other interesting refrigerant option in this proposed district energy system seems to be ammonia as none of the other refrigerants come close to the requirements. In the following a comparison of the properties between ammonia and CO2 is made, and an overview can be seen in Table 4 below.


Properties Ammonia CO2 Unit 𝑴𝒎𝒐𝒍𝒂𝒓 17 44 g/mol ODP/GWP 0/0 0/1 Safety group B2 A1 Tcrit 133 31.1 °C Pcrit 114.2 73.8 bar Cv at 8°C 4382 22545 kJ/m3 Cp at 8°C 2.805 2.366 kJ/kg Psat at 8°C 5.72 42.8 bar HVap at 8°C 1233 204.6 kJ/kg Δρ between vapor and liquid at 8°C 138.2 6.93

Table 4: Table of relevant properties of ammonia and CO2

As seen in the table, both refrigerants have their benefits and drawbacks, however on important properties such as volumetric heat capacity, density ratio and especially the toxicity, CO2 are clearly beneficial, though ammonia has the primarily advantages of higher specific heat capacity and operating at much lower pressures than CO2.

What is not covered in the property table is the ability to provide the desired energy services. Ammonia is very suited for refrigeration cycles as it has high latent heat capacity and low temperatures can be obtained at low pressures. However, problems occur when ammonia is used in a heat pump cycle to for instance heat water in households from low temperatures such as 8°C. Due to the risk of legionella the required condensing temperature of the heat pump has to be around 60°C, at least periodically. Obtaining temperature lifts from 8°C to 60°C is however not feasible with an ammonia heat pump. In smaller, non-industrial applications open type reciprocating compressors are used [28], and high temperature lift leads to an increased need for cooling of the compressor oil, which is undesired and expensive [29]. Large screw compressors are able to get around this problem with oil cooling, but these are only used in large industrial scale applications and not in small applications such as residential water heating [28].

In the end CO2 is the obvious choice as network refrigerant primarily due to the difference in safety group, especially considering that this network is expected to extend throughout densely populate areas, and safety must be the main concern. This is exactly the same reasoning that makes CO2 the standard for supermarket refrigeration systems.

12.3 Risk assessment An assessment of the risks in a potential CO2 district energy system is very important, as CO2 in a worst case scenario can be lethal to humans if exposed to high concentrations too long. According to Asger Lindholdt, Rambøll Risk and Safety division, [30] a full risk assessment job can normally take several months to carry out. In this case the system is very comprehensive and a full risk assessment would likely take much longer time to conduct. It is beyond the scope of this assignment to do so, but a shorter assessment highlighting the most important safety aspect regarding the CO2 district energy system will be made.

Information regarding risk assessment and safety issue of CO2 pipelines are sparse as transportation of CO2 is not that widespread, however Det Norske Veritas (DNV) has made a recent report on design and operation of CO2 pipelines in relation to Carbon Capture and Storage (CCS) technology[26], which is very


comprehensive and much of the information needed to do the risk assessment has been found in this report.

12.3.1 Risk assessment model Part of a risk assessment model has been adopted from Rambøll Risk and Safety division,[31], which will be used. The purpose of the model is to identify which potential hazards can occur in the system, how high the frequency of such occurrences are, and what measures can be taken and implemented to mitigate the potential risks. The model can be seen below in Figure 8.

Figure 8: Risk assessment model

A risk quantification of hazards in the CO2 pipeline network is very difficult to give as CO2 pipeline are extremely limited. The only practical experience is found in North America where they have 30 years of experience with CO2 pipelines, as this has been used for oil and gas extraction[26], but information regarding CO2 pipelines in urban areas has not been possible to find. Thus risk quantifications will in this assessment not be given, but it is important to consider if a more elaborate assessment is carried out.

12.3.1.1 Hazard identification Three major hazards groups have been identified from which several issues originate. The hazards can be seen below, and these are investigated in regards to the risk assessment model.

• Leakages from the pipeline • Leakages from decentral equipment • Corrosion in pipes or equipment

12.3.1.2 Leakages from the pipeline Leakages from the pipeline are a broad term, as the leakage can be small and insignificant, but also extreme with explosive decompression as result. These two cases are dealt with here separately.

12.3.1.2.1 Small leakages Small leakages could typically be in joints, sealings or gaskets where the pipeline is “weak”. Such could potentially be difficult to detect, but this depends on pressure drops at the site of leakage. Small leakages do not compose a high potential hazard to humans as the leaks are not likely to raise concentration of CO2 in the ambient air to concentrations level where humans are affected. In Table 5[32] the concentration of CO2 in the air, the exposure time on humans and the effect from being exposed to such concentration in the given time period are shown. The reference source does not provide specific details of the age, sex, fitness or general well-being of the people exposed.

RISK Hazard identification

Risk quantification

Mitigation measures


Table 5: Concentration of CO2 in the air, exposure time and effect on humans

Considering the normal CO2 concentration in the ambient air is 0.038% in the earth’s atmosphere [33], it is unlikely that small leaks can affect the health of humans.

12.3.1.2.1.1 Mitigation measures Small leaks can be difficult to detect, but measures can be taken to mitigate the potential hazards. For instance, pressure drop detection near “weak” parts of the pipeline, either in the form of pressure transducers or CO2 sensors is a possibility. Such measures however, would require many sensors or transducers, as there are numerous seal, joints and gasket along the pipeline. A cost benefit analysis would have to be carried out, where the risk quantification and cost of maintenance have to be included as well, to determine to what extent the mitigation measures must be carried out.

12.3.1.2.2 Large leakages Large leakages can cause severe accidents, which depend on the size of the hole in the pipeline. Such incidents could for instance happen if heavy machinery during digging around the pipeline accidently hit the pipe and it bursts.

If a large hole is made in the pipelines, CO2 will escape quickly and explosive decompression occurs as the CO2 pressure is 40-45 bar in the vapor and liquid lines respectively, and the ambient pressure is only 1 bar. This leads to very fast leaks of high concentrations of CO2 around the site of accident, and with CO2 having a density 50% higher than air at ambient conditions, the CO2 gas will stay at ground level and not rise, making the hazard even greater. In Figure 9 [26] the decompression speed of natural gas and CO2 can be seen, where it is noticeable that when CO2 reach vapor phase the decompression escalates fast.


Figure 9: Explosive decompression speed

If explosive decompression occurs the sound of CO2 escaping will be probably be high and alert workers and pedestrians. Additionally if the CO2 is colder than the water vapor in the ambient air, condensing of the water vapor will happen making the leak look like a cloud visible to the human eye, which increases the chance or notice [26]. However, when CO2 experience such rapid pressure drop, formation of solid particles will happen and if a person is hit by the high flowing stream of CO2, that person can get severe cryogenic burns on the skin or in the airways if inhaled [26]

12.3.1.2.2.1 Mitigation measures Mitigating the hazard of large leaks requires many measures, but some of the ones considered most important will be addressed.

Education and informing road workers or other people working near pipelines are essential, as these are the ones most likely to be exposed to high concentrations of CO2 if a large leak occurs. Evacuation plans involving local authorities, police, technicians, other relevant groups and inhabitants in a given radius must also be made. This is to ensure that everybody knows how to act, in order to reduce the number of persons exposed and the exposure time. If large leakages occur technical measures can be taken to reduce the amount of CO2 emitted to the ambient air by introducing block valves in the pipeline able to shut off the section where the leak has occurred. Figures showing the procedure can be seen in the combined Figure 10.


Figure 10: Control system with block valves reducing the amount of CO2 leaked to surroundings

Block valves can be installed in the pipeline with a certain distance in between, dividing it into control sections. A control system then measures the pressure before and after the valves and would be able to shut off the flow in the section with the leakage by closing the valves, if a significant pressure drop occurs. As shown in Figure 10 the control system also help venting the CO2 from the damaged pipeline section. The lengths of each control section depends on location, but as the proposed CO2 system is situated in densely populated area, the sections should most likely be relatively short, resulting in a high frequency. However, more sections also mean higher initial costs and more maintenance costs associated with doing so. A cost benefit analysis must therefore be made, to find the optimum frequency of control sections in regards to costs without compromising on safety.

12.3.1.3 Leakages from decentral machinery Leakages from decentral machinery probably constitute the largest hazard, as the machinery has supply directly from the CO2 pipelines and are likely to be placed in closed rooms such as basements. This combined with the fact that CO2 will stay at ground level and stay in the room, make leakages from decentral machinery very hazardous. During a leak, CO2 will slowly displace ambient air in the closed room, thereby increasing the concentration of CO2 which in worst case can be lethal if a person is exposed too long. From Table 5 it can be noted that CO2 will be lethal if the concentration is between 17-30% and an exposure time of less than a minute. CO2 is both without smell and color meaning it is difficult to detect, with the human senses [26].

12.3.1.3.1 Mitigation measures The dangerous hazards of leaks in decentral machinery, must be mitigated by using the same approach as with the large leakages - informative and technological. Informative mitigation obviously involves education and enlightenment of relevant persons such as; janitors, property managers and inhabitants, about the dangers involved with CO2 leaks and the precautions that must be taken when staying in or near the room with the energy service producing unit.

Technological mitigating measures must also be taken. CO2 sensors can be placed near the CO2 inlet and outlet pipes, and measure if concentrations become too high in the room. The sensors could perhaps be


connected to a ventilation system able to ventilate ambient air into the room and reduce concentrations of CO2. Shut off valves between the CO2 network and decentral equipment must also be in place, in order to reduce the amount of CO2 leaked. The valves could be controlled by pressure before and after the valves or in connection with the CO2 sensors. Another mitigating measure could be to put color in the CO2 or add smell, making it detectable to the human senses if leaks occur, but it is of great importance that the dye and smell-adding substance has no effect on the cycles, pipelines and other equipment.

12.3.1.4 Corrosion in pipes or equipment Corrosion in pipes or equipment is closely related to the two previous sections, as the resulting effect on human health also comes from leakages, but this section instead deals with hazards in regards to costs to avoid corrosion in pipes and equipment.

CO2 can cause deterioration to petroleum and many synthetic based lubricants found in valves, pumps, compressors etc. [26]. This hazard is especially critical to safety valves which could significantly affect the performance of the valves in emergency situations. CO2 is not corrosive in its chemical form to metal, but if dissolved in water, carbonic acid (H2CO3) will form, and this chemical compound is corrosive to carbon steel and low alloy steel [26]. CO2 and H2CO3 are however not corrosive to plastics or elastomers, but these are instead more sensitive to unwanted rapid expansions and decompressions in the system.

12.3.1.4.1 Mitigation measures With regards to the corrosion hazards with CO2 in pipes and equipment, material selection in every component of the system is crucial, as this can avoid more serious hazards affecting human health. In the pipelines, materials not corroded by H2CO3 are desired, or/and pipe wall thickness can be increased in sections where water content is more likely to occur. The proposed CO2 energy system is ideally a closed system with no direct interaction to the ambient environment, but water vapor could possibly enter somewhere in the system unintended. Water content control must be monitored to avoid formation of H2CO3, but the extent of this control is rather unknown, as the only reference system known is an open system in the oil and gas industry where water vapor can enter at the inlet together with the gas or crude oil.

12.3.2 Final risk assessment considerations Risk assessment of a potential CO2 district energy system will be very important to gain acceptance both from politicians and certainly also from the population. The threat of leakages, highly pressurized CO2 below the sidewalk and roads in the city, branch pipes from the network to machinery in basements and CO2 as an odorless, colorless gas able to suffocate humans at high concentrations are much likely to scare most people. Great examples of public resistance against CO2 are Vattenfall’s idea of making a CO2 storage in relation to carbon capture and storage (CCS) at Nordjyllandsværket north of Aalborg in 2009 [34] and DONGs plans of making a CO2 storage in Slesvig [35]. A risk assessment with proposed mitigation of all possible hazards is strictly necessary in order to gain acceptance, however it is problematic that there are no guidelines or experience of having a comprehensive CO2 network in an urban area. This leads to formulations of new guidelines which probably will relate strongly to similar risk assessments of natural gas and other widely used gasses, as well as the limited experience from the American oil and gas industry and


CCS projects. The question is whether it will be trustworthy enough to convince politicians and the population affected.

12.4 Pressure drops in distribution pipes Pressure drops in the transmission and distribution pipes with both H2O- and CO2 as the energy carrier are inevitable due friction losses between the pipe surfaces and fluid. This section investigates, through calculations, how much pressure drop can be expected in the pipes. Calculations are carried out in the simulation tool Engineering Equation Solver (EES) based on assumptions and information on district heating pipes provided by Rambøll, see Excel file “DN pipe table” The EES program code can be seen in EES file “Pressure drop district heating”

Calculations are divided into three parts; Firstly the allowed pressure drops will be determined, after which the pressure drops on the heating side and the cooling side are calculated. At the heating side, pressure drops in district heating pipes are compared to the ones in the CO2 vapor line, and at the cooling side, only pressure drops in the CO2 liquid line are considered as cooling is produced decentral in the water based system. In this investigation both systems has to transfer the same amount of energy in different sizes of district heating pipes.

12.4.1 Allowed pressure drops As a certain amount of pressure drops are unavoidable, the system has, as mentioned in section 12.1, been designed with a certain pressure difference between the two pipes. Table 6 below illustrates the allowed pressure drops in each pipe if isenthalpic conditions are assumed.

Liquid Vapor

T P h T P h C [bar] [kJ/kg] C [bar] [kJ/kg]

Pipe state point 8 45 219.9 8 40 432.8 Isenthalpic phase change 7.8 42.66 219.9 -3.6 31.63 432.8 Pressure drop allowed (ΔP) [bar] 2.34 8.37

Table 6: Allowed pressure drops before phase change begins at isenthalpic conditions.

It is obvious that the vapor pipe is far more stable than the liquid one. This is because the slope of the two different sides of the two phase area in the log ph diagram is different, see Appendix 8, which is quite beneficial in regards to this system, since the vapor pipe is the one where it is most important to avoid unintended phase change, since compressors generally does not handle liquid very well. In addition to allowing large pressure drops, the steep slope of the vapor line also leads to a relatively large temperature decrease occurring, which will also assist with avoiding condensation, since the low amount of assumed insulation would allow heat at ground temperatures to increase the temperature in the pipe.

If phase change should occur in the liquid line, it would not pose a problem since all cycles that use liquid as input throttles the pressure immediately in all circumstances, meaning that the only effect of unintended evaporation in the liquid pipe would be decrease system efficiency.


12.4.2 Pressure losses in pipes on heating side Calculations are based on the pipe types DN 25-300, which have variable diameters and designed flow velocities for water, provided by Rambøll.

The pressure drop in the H2O district heating pipeline have been calculated from the Colebrook equation in combination with the Darcy-Weisbach friction factor [36], as all the flows are turbulent, see EES file “Pressure drop district heating” The Colebrook equation can be seen below:

1�𝑓

= −2𝑙𝑜𝑔��

𝑘𝐷��

3.7+

2.51𝑅𝑒�𝑓

�

Where f is the Darcy Friction Factor and k is the roughness factor which is assumed to be 0.00005m for a steel pipe [37].

The Darcy Friction Factor is found iteratively with EES, and is used to find the head loss over a chosen distance from following equation [38].

∆𝑝 = 𝑓𝐿

𝐷��∗ 𝜌𝑣�

2

Where L is the distance over which the pressure drop is calculated; in this investigation 100 m is used.

The pressure drop in the CO2 vapor pipeline was calculated with the same equations and using the same pipe types, but in order to also have the same amount of energy transferred as in the H2O pipeline, the energy transferred in each pipe type was firstly calculated. The transferred energy was calculated assuming a ΔT = 50K between the supply and return pipe. The result was then multiplied with the mass of CO2 vapor needed to produce 1J in the open- and closed loop heat pump units, further described in sections 12.6.2.1 and 12.6.2.2, to find the needed mass flow. The masses of vapor were obtained from simulations of the various cycles, presented in Excel file “Simulation model” and only the best and worst case is considered in order to have the span of pressure drops.

The results of the pressure drop investigation in the H2O district heating pipes and CO2 vapor pipeline can be seen in Table 7 below.

Pressure drops in pipes on heating side Type Dinner L vw �̇� ΔPw ΔPvap min ΔPvap max Unit [m] [m] [m/s] [kJ/s] [bar] [bar] [bar]

DN25 0.0291 100 0.42 56.7 0.07821 0.29234 0.73697 DN50 0.0545 100 0.64 303 0.07891 0.30799 0.77801

DN100 0.1071 100 1 1828 0.08070 0.32593 0.82451 DN150 0.1603 100 1.29 5283 0.08081 0.33137 0.83874 DN200 0.2101 100 1.52 10694 0.08014 0.33133 0.83892 DN250 0.263 100 1.75 19292 0.08048 0.33487 0.84807 DN300 0.3127 100 1.95 30389 0.08078 0.33762 0.85515

Table 7: Pressure drops in district heating pipes of water and vapor CO2


As seen in Table 7, the pressure drop of water is relatively small and constant with the given diameters and flow velocities. Compared to the CO2 vapor line, water has between 5 to 10 times lower pressure drop depending on what heat pump unit is used to utilize the vapor CO2. It is however possible to minimize the pressure drops in the CO2 vapor line considerably.

12.4.3 Minimizing pressure loss in CO2 vapor line Significant pressure drops in the CO2 vapor pipeline are an important issue and will have a negative impact on the overall system performance, which must be minimized. The designed pressure in the pipeline is 40 bar and a temperature of 8°C, meaning close to 2.7K superheat. Pressure drops will lead to a need for increased compressor work to obtain the needed temperature, thereby decreasing the COP of the cycle, or in a worst case scenario liquid could form and enter the compressor which could lead to breakages.

As it was shown above, the CO2 vapor line has between 5 and 10 times higher pressure drops than water, but a few measures can be included to lower this effect. In this section it will be investigated how low pressure drops can be achieved by changing the inner pipe diameters of the CO2 pipes. H2O district heating pipeline needs a thick shell of insulation to avoid temperature losses, something the CO2 network does not need to the same extent due to operating temperature close to the soil temperature. By assuming that the CO2 pipeline is allowed to take up the same amount of space in the underground infrastructure as the H2O district heating pipes, the inner diameter is increased to match the diameters of DN 25-300 with insulation. It is also assumed that the inner steel pipes have the same thickness in both systems, even though it is very likely that the ones containing CO2 has to be thicker due to high pressures. Finally an insulation thickness of 10mm plus 3mm outer shell has been assumed for all CO2 pipes regardless of initial diameter. H2O district heating pipe diameters with insulation are from LOGSTOR A/S and given in [39], and includes two insulation thicknesses; insulation 2 and insulation 3. According to LOGSTOR A/S [40]modern district heating pipes use both insulation types, thus both has been included. Calculations have been carried out using the same EES code as previous section. Results of the calculation can be seen in Table 8 below, where the denotations “insulation 2” and “insulation 3” are the maximum inner diameter the CO2 pipes can attain when insulation and shell is included.

Pressure drops in vapor CO2 pipes

Type Dinner max insulation 2 ΔPvap min ΔPvap max

Dinner max insulation 3 ΔPvap min ΔPvap max

Unit [m] [bar] [bar] [m] [bar] [bar] DN25 0.0788 0.00219 0.005364 0.0938 0.00095 0.002298 DN50 0.1082 0.01029 0.02572 0.1282 0.00447 0.01112

DN100 0.1918 0.01796 0.04519 0.2168 0.009789 0.02458 DN150 0.246 0.03922 0.09900 0.281 0.02024 0.05103 DN200 0.32 0.04067 0.10275 0.365 0.02113 0.05333 DN250 0.414 0.03485 0.08807 0.464 0.01976 0.04988 DN300 0.4628 0.04775 0.12075 0.4828 0.03867 0.09777

Table 8: Pressure drops in the CO2 vapor pipeline using different pipe diameters

The highest pressure drop per 100 meter is 0.12075 bars, when using the least effective heating producing cycle, which is a very significant reduction compared to the initial investigation. By dividing the determine


maximum allowed pressure drop with the worst case scenario the minimum distance that the CO2 can be transported can be calculated.

𝐷�� =𝛥𝑃��

0.12075 · 100=

8.370.12075 · 100

= 6.9 [𝑘𝑚]

12.4.4 Pressure drops in pipes on cooling side Calculations of pressure drops in the CO2 liquid pipeline are made similarly from that of the CO2 vapor line, but no comparison can however be made with the H2O system as cooling is supplied differently. It is assumed that the liquid CO2 must deliver the same energy in the same pipes as the CO2 vapor and have the same insulation and shell thickness. The results can be seen in Table 9, and the EES code used to calculate the pressure drops can be found in EES file “Pressure drop cooling”

Pressure drops in liquid CO2 pipes Type Dinner max

insulation 2 ΔPliq Dinner max

insulation 3 ΔPliq

Unit [m] [bar] [m] [bar] DN25 0.0788 0.00222 0.0938 0.00093 DN50 0.1082 0.01106 0.1282 0.00466

DN100 0.1918 0.01973 0.2168 0.01052 DN150 0.246 0.04440 0.281 0.02236 DN200 0.32 0.04616 0.365 0.02342 DN250 0.414 0.03935 0.464 0.02186 DN300 0.4628 0.05456 0.4828 0.04385

Table 9: Pressure drops in the liquid CO2 pipeline using different pipe diameters

The highest pressure drop per 100 meter is 0.05456 bar when using a DN 300 pipe which is reasonably considered low. Again the possible transport distance is calculated..

𝐷�� =𝑑𝑃��

0.12075 · 100=

2.340.05456 · 100

= 4.3 [𝑘𝑚]

12.4.5 Final remarks The CO2 system is more sensitive to pressure changes than the water base system because the operating pressure and temperature is close to the saturation point, but with the described assumptions it has been determined that the minimum distances that the CO2 can be transported before phase change commences is far greater, than what will be necessary in a densely populated area. Since all units are assumed to release the CO2 at the appropriate pressure, then they all contribute to keeping the pressure at the desired level throughout the system, meaning that as long as consumers are placed closer together that the calculated 6.9 km and 4.3 km respectively, then pressure drops should not cause concern.

The pipe diameters could even be smaller than the ones analyzed, if the consumer density and demand patterns allow it, however such calculations would only be possible if the area in question is well defined during the planning phase.


Having pumps and compressor in the CO2 pipelines to balance pressure if needed cannot be avoided even though the pressure drops are small. A situation where many consumers need the same energy service at the same time can create a sudden mass flow and result in a pressure drop, which requires balancing equipment along the pipeline. It has however been assumed that the electricity used for these auxiliary pumps and compressors will only make up a very small fraction of the total electricity demand, and in addition be subjected to both energy systems, leading to it not being included for any of the systems in the simulations.

12.5 Plant side In the following sections the central vapor and liquid production from the Avedøre CHP plant and the sea are explained. System diagrams, results and cycle illustrations of each cycle will be presented along with assumptions and considerations made in order to give an overview of the plant side production units in the CO2 system.

12.5.1 Vapor production CO2 vapor can be produced directly from liquid CO2 if a heat source higher than the evaporation temperature of 5.3°C is available. As mentioned the CHP plant Avedøre Block 1 has been chosen to supply electricity and heat to the proposed CO2 system to the extent possible. Electricity is, as is the case with the H2O based system, the dimensioning size for the CHP plant, since it is the only balancing production unit with regard to electricity, whereas thermal demands can be satisfied by other means. Additionally, the cold producing units disposes electricity as heat, thereby adding more vapor to the CO2 vapor line, which reduces the need for heat production from the plant side. The CHP plant will be able to cover most of the heat production to balance the system, but at times where it is not possible, the sea will be used as heat source to produce CO2 vapor. The two vapor productions units, the CHP and the sea, will be explained further in the following sections.

12.5.1.1 CHP vapor production The following sections only present the system diagram, performance of the CHP heat exchanger and a cycle illustration. A cycle description including heat exchanger considerations can be found in Appendix 9. Additionally a more thorough explanation of the Avedøre CHP plant block 1 can be found in section 14.1.1 together with all other production units included in both of the energy systems.

12.5.1.1.1 Purpose The purpose of vapor production at the plant side is to fulfill the remaining heat demand after the synergy effect has been taken into account, by utilizing the excess heat from the CHP production to evaporate CO2 liquid.

12.5.1.1.2 System diagram The system diagram in Figure 11 shows liquid CO2 being evaporated to the vapor CO2 line from the excess heat from the electricity production. Numbers in the diagram is DNA nodes and the DNA model of the heat exchanger can be found at the end of Appendix 9 or DNA file “PlantsideHEX”


Figure 11: System diagram showing heat exchanger at plant side to produce vapor CO2

12.5.1.1.3 Results The most relevant results are shown in Table 10 below.

Plant side heat exchanger Unit

�̇� 80 kJ/s Tin CHP 29.8 °C Tout CHP 29.8 °C PCHP 0.042 bar

�̇�CO2 0.28 kg/s

�̇�H2O 0.03 kg/s Table 10: CO2 evaporating heat exchanger results

Due to the very low pressure of the warm vaporized water from the CHP plant, condensation takes place with CO2 as the heat sink. This means the mass flow of water does not need to be high due the considerable amount of latent heat energy available when changing phase.

12.5.1.1.4 Cycle illustration

Figure 12: T,s diagram showing illustration of the plant side heat exchanger cycle


Figure 12 shows the heat exchanger cycle in an T,s diagram, where the red curve is the excess heat from the power production, where the power plant run in full condense mode. The black curve shows the liquid CO2 being throttled down and evaporated.

12.5.1.2 Sea based vapor production

12.5.1.2.1 Purpose During the winter, consumers could have heat demands in excess of what the CHP plant can produce. In that case, energy can be extracted from the sea, a lake or a ground source loop, to evaporate the needed amount of CO2. Dependent on the temperature of the available source, the evaporation can either be conducted directly using only a valve and an evaporator, or alternatively assisted by compressors which will increase the electricity demand.

12.5.1.2.2 System diagram The two different possibilities are illustrated in Figure 13 below with notes from DNA. DNA code can be found in DNA file “CO2_Vapor_SeaWater”.

Figure 13: Vapor production from the sea or the ground dependent on available temperature level.

The temperature needed for direct evaporation is above approximately 5.3°C, meaning that the temperature at the bottom of the sea usually will be adequate to some degree, it should however be considered that when the temperature difference between evaporation and the sea becomes small, the size of the evaporator and needed amount of water will become problematic. To assess this problem, simulations have been done for all the temperature steps, using both the direct and compressor driven approach and scaled to deliver the maximum needed vapor production needed throughout the year.


12.5.1.2.3 Results The final results are presented in Table 17 below.

Tsw in Tsw out �̇�sw COP [C] [C] [kg/s]

Direct 8 6.5 889.29 26.22 Compressor 8 4 346.1 33.38 Direct 9 6.5 542.2 43.38 Compressor 9 5 345.42 41.60 Direct 10 6.5 388.53 60.54 Compressor 10 6 341.82 54.79 Direct 11 6.5 302.75 77.68 Compressor 11 6 273.92 64.90 Direct 12 6.5 248.01 94.82 Compressor 12 6 228.53 74.02

Table 11: Efficiencies in central vapor production based on water from the sea

It is clear, that even though it is possible to use only the direct approach, when the temperature of the sea reaches 8°C the COP of the direct approach is actually worse than the compressor driven one. This is caused by the huge amount of water needed, meaning that the pump power used becomes greater than the power needed to drive the compressor. Based on the mass flow considerations mentioned in section 0, it is chosen that while the water temperature is below 10°C, the compressor driven approach will be utilized, at or above 10°C the direct evaporation is chosen.

12.5.1.2.4 Cycle Illustration The top cycle illustration shows direct evaporation of CO2, the black line, with water temperatures of 8°C and 12°C, the blue lines, and the bottom illustration shows compressor driven evaporation of CO2 with the same water temperatures. The advantage of including the water lines on the illustrations is that it is possible to see that no crossing of the lines takes place, which would indicate that the 2nd law of thermodynamic was violated.

Figure 14: T-s diagram for direct evaporation at hot source temperatures from 8C to 12C


Figure 15: T-s diagram for compressor driven evaporation at hot source temperatures from 8°C to 12°C


12.5.2 Central Liquid Production

12.5.2.1 Purpose During the summer, the consumers could in some periods have excess demand for cooling capacity, meaning that vapor must be condensed into liquid centrally to balance out consumption. In case a cold source below 5.3°C is available, the vapor can be condensed directly at vapor line pressure and then pumped to the liquid line afterwards, making the process very efficient. However, often the excess cooling demand will coincide with high ambient temperatures, meaning that the available cold sources will rarely be below 5.3°C, resulting in a need for increasing the condensation temperature of the CO2. This is achieved be compressing the vapor additionally until a satisfactory condensation temperature is obtained, and then throttling the liquid back to liquid pressure.

Based on measured data from the bottom of the Danish sea near Copenhagen, see Figure 17, obtained from [41], the average temperature for an entire year is 9.53°C, with a minimum of 7.98°C and a maximum of 12.5°C, see Excel file “Sea water temperatures 2009”. This temperature interval is divided into steps of 1K and a corresponding COP is determined for each temperature step. The intervals are illustrated in Table 12 below. To ensure that the temperature steps are reasonable representations the yearly average of the steps is found to be 9.49°C, meaning that the divergence on a yearly basis is in the range of 0.04 K.

Temperature interval

Temperature step

[°C] [°C] TW < 8.5 8

8.5 < TW < 9.5 9 9.5 < TW < 10.5 10

10.5 < TW < 11.5 11 TW > 11.5 12

Table 12: Temperature steps used in simulations

12.5.2.2 System diagram The two different possibilities are illustrated in Figure 13 below with notes from DNA. DNA code can be found in DNA file “CO2_liq_SeaWater”:

Figure 16: Liquid production from sea or ground dependent on temperature


12.5.2.3 Results The final results are presented in Table 17 below.

Tsw in Tsw out �̇�sw COP

[C] [C] [kg/s] [-] Direct 0 5 736.5 66.30 Compressor 8 18 363.57 12.32 Compressor 9 19 362.82 11.46 Compressor 10 20 362.73 10.72 Compressor 11 21 362.97 10.08 Compressor 12 22 363.37 9.76

Table 13: Efficiencies in central liquid production based on varying temperatures of water from the sea

It is obvious that the direct condensation is far more efficient, meaning that in situations where a cold source below 5.3°C is available, it should be utilized. However as can be seen in Figure 17, showing the obtained sea water temperatures at a depth of 28m near the Danish island Ven, the temperature at the bottom of the sea never reaches below approximately 8°C, making that possibility unusable in the further simulations.

Figure 17: Sea water temperatures throughout the year at a depth of 28m near Ven

Another possibility could be to use surface water which approaches 0°C in the winter time, however obviously, and as is illustrated in Figure 36 bottom graph, the excess cooling demand primarily occurs during the summer, where the surface water is warmer than at the bottom, just as the excess demand for heating occurs during the winter, making the lower surface temperatures at that time undesirable. In short the temperature fluctuations at the surface of the sea are inverted when compared to the demand pattern.

To get an idea of the amount of water that it is possible to deliver to a central production plant, the district cooling central near Kongens Nytorv is used as a guide line. This plant is located on the site of an old power plant and relies on the old cooling water supply pipes leading to the harbor to obtain the needed amount of cooling water for all three utilized cooling technologies [42]. In full operation the plant consumes the amount of cooling water listed in Table 14 below.


Technology [m3/h] [kg/s] Absorption 887 252.5 Free/Direct 172 49.0 Compressor 522 148.6 Total 1581 450.1

Table 14: Cooling water use at Kgs. Nytorv district cooling plant in full operation

The plant does however not operate all three technologies at the same time, since the sea water temperature is too high during the summer to be used for direct cooling purposes [8], instead only the absorption and compressor chillers are operated simultaneously, resulting in a maximum transported amount of water close to 400 kg/s, which is far less than needed for direct cooling based on a 0°C source. It is assumed that it will be feasible to produce liquid in all the other cases, where compressors increase the condensing temperature, thereby lowering the needed amount of water.

For the rest of the simulations the COP corresponding to the specific sea temperature at the bottom will be utilized, since this is assumed to be the best easily available source.

12.5.2.4 Cycle Illustration In Figure 18 below, liquid production at three different temperatures are illustrated. The top one is in case where the maximum temperature step of 12°C sea water is available; the middle one is the case where the minimum temperature step of 8°C is available, thereby illustrating the two extremes between which the liquid production will take place. The bottom illustration is the case where a 0°C cold source is available, making is possible to condense the CO2 directly without the use of a compressor.

Figure 18: Illustration of the different liquid production possibilities

It is obvious that when condensing CO2 at temperatures above 8⁰C, then 8⁰C cannot be reached as the CO2 output temperature. In fact when utilizing 12⁰C seawater, then the CO2 is initially only cooled to 13⁰C, after which a throttling valve lowers the pressure into the two phase region, evaporating 2.8 % of the CO2 and


thereby cooling the CO2 to 10⁰C, before it is sent to the network. This is accepted because as it is explained in section 12.4.1, a small amount of evaporation in the liquid pipe does not pose a problem for the system, except with regard to the overall system performance. To take the effect of this into account, the COP of the sea based liquid production is decreased accordingly, ensuring that the final simulation results include the discrepancy.

12.6 Consumer side From the consumer’s point of view, the proposed system requires more specific machinery to obtain the desired energy service by utilizing the phase change energy of CO2. Heating is produced from either open- or closed loop heat pumps, refrigeration is produced from a refrigeration system and comfort cooling just from a heat exchanger. The following sections describe each cycle briefly and presents cycle performance results and cycle illustration.

12.6.1 Cooling demand Cooling is in the CO2 system delivered by evaporating liquid CO2 thereby removing heat from the cold producing cycles. Two different types of cooling cycles are included in the CO2 based district energy network – Comfort Cooling (CC) and refrigeration (REFRI).

12.6.1.1 Comfort Cooling – CC The following sections briefly present the main aspects, but a cycle description including choice of heat exchanger can be found in Appendix 10.

12.6.1.1.1 Purpose In supermarkets, malls, shops and office buildings heat emitting sources such as humans, appliances, lighting and solar irradiation make the temperature rise in the rooms and creates a need for comfort cooling to maintain a comfortable temperature. The CO2 system is able to provide the needed comfort cooling very efficient and easy, as CO2 liquid can be throttled down, evaporated and returned to the vapor line without use of any additional machinery than a valve and a heat exchanger. Since the liquid line has a higher pressure than the vapor line a natural flow will occur through the heat exchanger.

12.6.1.1.2 System diagram In the following section the system diagram is shown in Figure 19 with DNA nodes. The DNA code can be found in end of Appendix 10 or DNA file “CO2_ComfortCooling”

Figure 19: System diagram of comfort cooling loop with nodes used in DNA code


12.6.1.1.3 Results In the following Table 15 the main results of the CC cycle are shown.

CC cycle Unit

Media H2O Tin 18 °C Tout 10 °C

�̇� 80 kW

�̇�CO2 0.38 kg/s

�̇�H2O 2.42 kg/s Table 15: Results of the CC cycle

It can be noted from Table 15 that the mass flow of water is noticeably higher than the CO2. The reason is that the enthalpy change from evaporating CO2 compared to cooling water is much higher and proportional to the mass flow ratio.

12.6.1.1.4 Cycle illustration

Figure 20: T,s diagram of CO2 showing water being cooled from 18°C to 10°C

In Figure 20, a T,s diagram of CO2 is shown. The black curve represents liquid CO2 being evaporated from the liquid supply line to the vapor line. The blue curve represents water being cooled from 18°C to 10°C.

12.6.1.2 Refrigeration The following sections briefly present the main aspects of the refrigeration cycle, but a description including cycle components can be found in Appendix 11.


12.6.1.2.1 Purpose The current standard way of obtaining refrigeration is to use electrically driven compression cycles, condensing the refrigerant outside in forced convection air condensers, thereby loosing the produced surplus energy. This leads to a range of less than optimal circumstances, the main one being that the efficiency of the system can be heavily decreased in case of hot weather, which corresponds to the time where a high refrigeration requirements are present.

In the proposed system, the thermal energy being extracted from the refrigerated areas are stored as latent energy in the CO2 system’s vapor line, which has the added benefit that the efficiency of the cycle is not directly dependent on the outside conditions.

12.6.1.2.2 System diagram The proposed cycle is almost the same as explained in section 11.3.3.3.2, the main difference being that the outside air cooled condenser has been replaced with connection to the CO2 network. The system diagram is shown with DNA nodes, and the DNA code can be found at the end of Appendix 11 or DNA file “CO2_Refri”

Figure 21: System diagram of refrigeration cycle in the CO2 based system

12.6.1.2.3 Results Based on the mentioned considerations, the refrigeration system has been modeled in DNA, resulting in the following values.

Refrigeration cycle

LP HP Units Tevap -35 -15 °C

Tsuc -30 -1.1 °C

Tout 28.21 48.19 °C

�̇� 20 60 kJ/s

�̇�CO2 0.09 0.36 kg/s

W 4.02 12.78 kW

COP 4.98 4.69 Overall COP 4.76

Table 16: Final refrigeration cycle results


12.6.1.2.4 Cycle Illustration In Figure 22 the refrigeration cycle, consisting of a cooling and freezing cycle, is illustrated in a Ts diagram. The green line represents the cooling cycle and the light blue represents the freezing cycle.

Figure 22: Cycle representation of the refrigeration cycle in a T, s diagram.

12.6.2 Heating demand In the proposed system heat can be produced by two different heat pump cycles - open loop heat pump and closed loop heat pump. The heat produced is used for space heating and domestic hot water meaning the cycles are optimized with the assumption that heat is only produced to meet the temperature requirements of these demands. Production of steam is not dealt with in this assignment, as there is no demand for steam with the consumer types considered. The two different types of heat pumps are presented in the following two sections, along with assumptions, considerations and calculations.

12.6.2.1 Open Loop Domestic Hot Water – OLDHW The following sections briefly present the main aspects, but a description including cycle components can be found in Appendix 13.

12.6.2.1.1 Purpose The purpose of the Open Loop Domestic Hot Water (OLDHW) heat pump is to supply consumers with hot water, both for space heating (SH) and domestic hot water (DHW) purposes. These two purposes are very similar, but there is a very crucial difference which must be considered when simulating the system. The DHW consumption is considered heated from an ambient ground temperature assumed to be 8⁰C, whereas the SH has a return loop from the building, meaning that the space heating is only heated from an assumed return temperature of 40⁰C [43]. In large building complexes the DHW is also circulated, but as a simplification the circulation pipes are assumed to be insulated adequately to eliminate excessive heat loss, meaning that only the consumed water must be heated.


12.6.2.1.2 System diagram There are two different system varieties considered, one using an expander which could possibly increase the systems COP, and another more standard cycle utilizing a valve to decrease pressure. Numbers are from the DNA code and can be found at the end of Appendix 13 or DNA file “OLDHW_valveSepa”, .

Figure 23: Refrigeration system schematics for the CO2 system, one with expander and another with valve implemented, the numbers correspond to nodes in the DNA code.

12.6.2.1.3 Results The final results are presented in Table 17 below.

Open loop cycle 8°C -60°C 40°C -60°C Units Tcomp out 85 100 °C

Tsup 8 8 K

Tliq 10 10 °C

�̇� 80 80 kJ/s

�̇�CO2 0.32 0.26 kg/s

�̇�H2O 0.37 0.96 kg/s

W 16 26.63 kW

COP 5 3 - Table 17: Final cycle results for the OLDHW unit

As can be seen, the CO2 system benefits heavily from low return temperatures, meaning that this setup is primarily suited for DHW production, while still performing adequately in regard to SH.


12.6.2.1.4 Cycle Illustration The final cycles are illustrated below, where the black line is the CO2 cycle and the blue is the water being heated. In the current simulations the lowest temperature difference is 4⁰C and 1⁰C for DHW and SH respectively.

Figure 24: Cycle illustration in a T, s diagram of CO2 showing domestic water heating from 8°C to 60°C


12.6.2.2 Closed Loop Domestic Hot Water – CLDHW The following sections briefly present the main aspects of the cycle, but a description of cycle component and refrigerant considerations can be found in Appendix 15

12.6.2.2.1 Purpose This cycle is called closed loop domestic hot water (CLDHW) because it has a closed loop between the CO2 network and the water heating loop to and from the consumers. The closed loop cycle is advantageous at times when return water from the customers are high, leading to only small temperature lifts being needed, where subcritical operation can severely increase performance.


12.6.2.2.2 System diagram The system diagram including nodes used in DNA is shown in Figure 26 below, the DNA code can be found in the end of Appendix 15 or DNA file “Closed_loop_8_60” and “Closed_loop_40_60”, .

Figure 26: System diagram of closed loop cycle with DNA notes

The cycle illustration seems a bit complex, which is cause by the fact that the CO2 is condensed directly at vapor pressure, meaning 5.3°C, making it impossible to obtain the desired 8°C in the liquid line after use. Therefore an extra heat exchanger is implemented before the expansion valve, thereby utilizing the remaining heat from the Propane to obtain the desired output temperature.

12.6.2.2.3 Results The closed loop cycle has been modeled in DNA including relevant input parameters Table 18 below presents the most relevant results.

Closed Loop Domestic Hot Water cycle 8°C -60°C 40°C -60°C Units Refrigerant Propane Propane

Tevap 0 0 °C

Tcond 53 55 °C

Tsup 20 40 K

Tsub 28 10 K

�̇� 80 80 kW

�̇�CO2 0.27 0.28 kg/s

�̇�prop 0.18 0.18 kg/s

�̇�H2O 0.37 0.96 kg/s

W 18.7 21.38 kW

COP 4.28 3.74 Table 18: Results of the closed loop cycle


12.6.2.2.4 Cycle Illustration In the Figure 27 and Figure 28 the closed loop cycle is shown in a T,s diagram with the nodes used in DNA. The black curve is the propane cycle, and the blue curve is water being heated from 8°C to 60°C and 40°C to 60°C respectively.

Figure 27: T, s diagram of propane showing water being heated from 8°C to 60°C



13 Case description After having described how the thermal demands will be met in each of the systems, a case model is constructed that specifies the magnitude of each demand for every hour throughout the year. In the following sections the basic assumptions of this case model will be presented to provide an understanding of the boundaries and composition of the system. The consumption patterns of the chosen consumer types will also be briefly described, as well as the final consumption pattern presented.

13.1 Basic assumptions The reason for constructing the case is that it is seen as the best way to compare the two energy systems. By expecting them to deliver realistic energy service demands throughout an entire year, based as closely as possible on real consumption values, the systems are compared on the most relevant basis imaginable. This approach is seen as the best way to simplify comparison of two complex energy systems in a controlled way without favoring one system or the other.

By comparing the needed yearly energy input for each system, the systems overall efficiency can be determined and compared.

In this case it is assumed that an area of 1,000,000m2, which corresponds to 2.75% of the floor space in Copenhagen[44], must be satisfied with electricity and the thermal energy services, space heating, domestic hot water, comfort cooling and refrigeration on an hourly basis. Copenhagen is chosen as the case location as required data are available to a larger extent than any other city in Denmark.

To have a variety of energy services and to replicate the consumer composition as well as possible, it has been chosen to have 4 different consumer types – residential buildings, supermarkets, malls and office buildings. In Copenhagen the rough distribution is 62% residential buildings and 38% commercial buildings, [44], but due to the large variety of uses in the commercial sector a simplification has been made, so that the size of retail trade is determined based on numbers from a survey made [45], and the remaining area is considered to be office buildings. The building distribution in the basis scenario of the case study can be seen in Table 19.

Consumer [%] Residential 62 Mall 1 Supermarket 4 Office 33

Table 19: Distribution of building area in Copenhagen

Table 20 below shows an overview of the thermal energy service needs for each of the consumer types considered.

Customer Hot water Space heating Refrigeration Comfort cooling Residential buildings X X Malls X X X Office buildings X X X Supermarket X X X X

Table 20: Energy services needed in the included consumers


13.2 Consumption Consumption data for each of the thermal energy services from each consumer type has been obtained from several different sources, mentioned in the respective sections. Unfortunately it has not been possible to obtain hourly data for most of the consumption of the thermal energy services. The most likely reason for this is that very few measurements are carried out in general and if measurements are carried out, it has likely been done by a company with energy optimization purposes, and they have not been willing to disclose the information from their customers. It has however been possible to obtain some data for each energy service for each consumer type, and this data has been used to make hourly data series based on assumptions made. The assumptions and procedures deriving hourly consumption data of each consumer type are described more detailed in Appendix 17-21.

Total electricity consumption data were more easily obtained from [46] where total electricity consumption for Eastern Denmark has been scaled down to match the area in the case. Numbers used for scaling are from [44]. In order to obtain data for electricity demand for uses not related to thermal energy services, the electricity consumption used for refrigeration and comfort cooling has been determined based on efficiencies for the H2O system and then subtracted from the total power consumption. These calculations are carried out in DNA, see Appendix 6 and Appendix 3 for program code or DNA files “H2O REFRI” and “H2O comfort cooling”, and in the simulation model, see Excel file “Simulation model”

Weather data from a reference year with particular interest with regards to ambient temperatures and solar irradiance has been obtained from [47]

Difficulties obtaining the desired consumption data, has also led to inconsistency of matching reference years, meaning that consumption and weather data are not necessarily from the same reference year. It is however assumed that the influence on the overall performance of the systems and the system comparison will be insignificant over an entire year, even though the timing between consumption and production may be affected in some hours.

In the following sections a short description of the consumer types will be given, and a plot of the hourly consumption patterns is presented.


13.2.1 Mall As a model for the consumption pattern of a mall, consumption values from Fields in Copenhagen are utilized for the comfort cooling, whereas the space heating and domestic hot water consumption is assumed to be similar to that determined for office buildings. A more detailed description of the data obtained and derivation of hourly consumption patterns of the different energy services can be found in Appendix 17. A plot of the hourly consumption pattern of the mall is illustrated in Figure 29 below:

Figure 29: Area specific hourly consumption values for a mall

It should be noticed that the values in the figure are represented as a per m2 value. This is done to make it possible to scale the size of the simulated area at a later point in time.

13.2.2 Supermarket Supermarkets are the only consumer type in this case which have needs for all four energy services; Space heating, domestic hot water, comfort cooling and refrigeration. To estimate the hourly consumption pattern for each of these thermal energy services, data has been obtained from a Føtex in Frederikssund, provided by Jesper Thorsgaard Larsen from Dansk Supermarked. See Appendix 19. Hourly consumption data has been derived from the data given, and a more detailed description of the derivation can be found in Appendix 18. A plot of the hourly consumption pattern of the supermarket is illustrated in Figure 30 below.

Figure 30: Area specific hourly consumption values for a supermarket


13.2.3 Office In order to estimate the hourly consumption of space heating, domestic hot water and comfort cooling for office buildings, data from two new low-energy office buildings has been obtained from Rambøll, based on simulations in Integrated Energy Solutions (IES), see Excel file “Office building consumption” . These data include both space heating and comfort cooling requirements on an hourly basis, leaving only the hourly demand for domestic hot water to be derived. A description of derivation of this can be found in Appendix 20. A plot of the hourly consumption pattern for office buildings is illustrated in Figure 31 below.

Figure 31: Yearly consumption pattern for office buildings

13.2.4 Residential To estimate the hourly consumption pattern in residential buildings, monthly data from two building blocks has been provided by the energy group at Dansk Almennyttig Boligselskab (DAB). The data is from the building blocks “Værebro” and “Høje Søborg II” and only given as the total heat consumption, thus including both space heating and domestic hot water, see Excel file “Residential consumption” No comfort cooling or refrigeration demand is assumed for residential buildings. A more detailed description of the derivation of the hourly consumption data in residential buildings can be seen in Appendix 21. The hourly consumption pattern for residential buildings is illustrated in Figure 32 below.

Figure 32: Space heating and hot water consumption per m2 in the residential sector.


13.3 Final Consumption Pattern The final consumption pattern consists of consumption data from each consumer type added together, which gives an hourly consumption pattern of each thermal energy service and electricity for non-thermal uses. The demand has been scaled to cover 1,000,000 m2 which the case area has, but the ratio between the energy services remain the same no matter the size of the scaling.

The final consumption pattern shows coherence with what could be expected, with rather constant demand for domestic hot water and refrigeration and fluctuating demand for space heating and comfort cooling throughout the year as these are highly temperature dependent. It should be noted that the heat demand is generally much higher than cooling demand, with the exception of few hours during the summer.

The final consumption pattern is illustrated in Figure 33 below.

Figure 33: Final consumption pattern for 1,000,000 m2 area in the case model.

This consumption pattern will serve as the demand that each system must fulfill, while being compared on the energy input needed to deliver these services.


14 Available production units The Danish energy system is highly complex, and a range of simplifications have been made to make the simulations possible, in the following sections the assumptions regarding the different production facilities will be relatively briefly explained, for more extensive information see Appendix 22.

The energy production for the systems is very similar with only small differences in the way they are implemented. In the following section all the utilized production technologies will be clarified, each with a set of assumptions, possibilities and limitations to consider.

14.1.1 Thermal electricity production

14.1.1.1 Assumption 1: Coal as fossil fuel The thermally based electricity production is considered as the primary input and is also the one used for balancing production and consumption after the intermittent sources have been subtracted from the demand, for more information on this procedure see Excel file “Simulation model”. Coal has been chosen as fuel since it currently represents 40% of the Danish primary fuel consumption for electricity production [48]. The exact distribution for electricity production in Eastern Denmark in 2009 can be seen in Table 21 below.

Source [%] Coal 40 Natural Gas 17 Wind 14 Water 4 Sun 0 Waste, Biomass Biogas 13 Oil 5 Nuclear 7

Table 21: Fuel distribution for electricity production Eastern Denmark 2010

The thermal production is modeled after the CHP plant Avedøre block 1, which is located in Copenhagen and has been supplying heat and electricity to the area since 1990. The plant can vary production between pure power production called condensing mode and CHP production called back pressure mode, which ensures optimal possibilities for balancing demand and consumption throughout the year.

It should be noticed that using coal as the only fuel does not influence the results since it merely serves as a more manageable illustration of the energy consumption. The simulations also return the needed primary energy input, which can be satisfied by any fuel while the ratio between the systems fuel consumption will remain the same.


14.1.1.2 Assumption 2: Large number of plants leads to infinite electrical scalability There are however a range of limitations to the possible production situations, which must be taken into account when simulating the system performances throughout the year. Table 22 shows the full load specifications for Avedøre CHP plant block 1, while Figure 34 illustrates a set of simplified information about the operational parameters within which the plant can operate.

Avedøre CHP plant block 1 Fuel input Coal 595 [MJ/s]

ηFCM 42 [%] ηFBP 91 [%] Output FCM Electricity 250 [MW]

Output FBP Electricity 215 [MW]

Heat 330 [MJ/s] Table 22: Full load specifications for Avedøre CHP plant block 1.

Figure 34: Avedøre CHP plant block 1 production modes

The plant has a maximum output which can be varied between 250 MW electricity and no heat or 215 MW electricity and 330 MJ/s heat, meaning than any state between these two points are possible. This also means that the COP of the heat produced from the CHP plant can be easily calculated.

𝐶𝑂𝑃�� =330 − 0

250 − 215=

33035

= 9.43

This is a very high COP, which is why CHP production is so very efficient. In the result section it will be illustrated how large an advantage this COP actually is.

When decreasing output demands the plant can only operate down to a power to heat ratio of 0.65, meaning that the power output divided with the heat output must remain above this value. The minimum load is chosen to be 50 % of the full load because further decrease would cause excessive decline in


efficiency, in actuality this value is a bit lower, but due to the following assumptions this will not influence the results.

As seen in Figure 34, all situations where the power to heat ratio is above 0.65 can be reached, assuming the demanded power is within the plants operational limits, whereas any situation where the ratio is below that it is impossible to satisfy demand. This difference becomes even more pronounced when considering that the power production can be scaled by assuming that a number of plants work together to meet demand. Then the minimum production would stay the same, the maximum would increase with the number of plants, while the slope of the full back pressure line would remain unchanged meaning that excess heat demand would remain in the unreachable region.

This is the reasoning behind the assumption that the size of demand does not influence the efficiency of the production unit whereas the ratio between power and heat demand does. Figure 35 below shows a plot of all the 8760 hours of heat and power demand plotted against the constraints of the CHP plant.

Figure 35: Possible production scenarios with three CHP plants combined

In the example illustrated in Figure 35, three plants are included, one with a maximum heat production of 5000 kJ/s and two identical ones with a max production of 10000 kJ/s, leading to a situation where electricity demands can be met for all hours of the year. The operational limits of this setup are indicated in Table 23 below.

Example of full load specifications for the described system

Power Heat [kW] [kJ/s]

Back pressure Minimum production 1629 2500 Maximum production 16288 25000

Condensing mode Minimum production 1894 0 Maximum production 18940 0

Table 23: Operational limits of a system including 3 CHP plants, one with a maximum heat production of 5000 kJ/s and two with a maximum heat production of 10000 kJ/s


It is obvious that a significant number of the hours are below the line indicating possible production situations, in fact, 37% of the time it is impossible to meet district heating demand with only CHP production.

In the CO2 system the power plant will always run in full condensing mode because the condensing temperature is warm enough to allow for direct evaporation of CO2. The system is then regulated by varying the amount of power plant cooling water used for evaporation or being cooled directly by seawater. Using this approach 99.3% of the total thermal energy consumption in the CO2 system can be covered by the CHP and renewable energy sources, leaving only 0.7% to be covered by energy exchange with seawater.

14.1.1.3 Assumption 3: Storage One way to solve this limitation is to include hot water storage tanks which are heated when demand is low and can then assist production in peak hours. This solution is a very cheap way to increase the utilization of CHP district heating production, but is of course highly dependent on the size of storage.

In the most basic scenario, the size of the storage included is scaled according to the maximum production rate of Avedøre CHP plant block 1, which has a storage capacity corresponding to 2.27 hours of full production based on the values described in Table 24 [49].

Storage calculations

Vw Avedøre 44000 [m3]

ΔT storage 40 [K]

Cp w 4.2 [kJ/kg-K]

Qstorage Avedøre 7392000000 [kJ]

�̇�heat max Avedøre 905 [MJ/s]

Number of full load hours 2.27 [h] Table 24: Values used for the calculation of storage size

The 2.27 hours are then multiplied with the largest hourly heat demand throughout the year to determine an appropriate storage size for the scenario.

14.1.1.4 Assumption 4: Boilers as a last balancing measure In situations where the CHP production and storage contribution is insufficient, boilers are utilized to cover the remaining heat demand by burning the coal directly without electricity production. This is generally undesired, and will only take place when all other possibilities are exhausted.

In the CO2 system, sea water energy exchange takes the place of boilers as the last resort when trying to balance the system.

14.1.2 Wind power To determine the amount of wind production to include, the overall 2009 production distribution presented in Table 21 is utilized, which specifies that the total electricity production from wind in Eastern Denmark was 14% [3]. This percentage is converted into a specific amount of electricity by multiplying with the total consumption of 2009. This value is then allocated to Copenhagen based on the number of


inhabitants in the entire Eastern Denmark compared to Copenhagen, and then further distributed onto the chosen simulated area. With these considerations, the chosen area of 1,000,000 m2 represents 0.625 % of the total electricity consumption of Eastern Denmark.

𝑃𝑃�� = Φ�� [%] ∙ 𝑃𝑃�� ∙𝑁��

𝑁��∙

𝐴��𝐴��

This leads to a total yearly production, which is then distributed onto the hours of the year by multiplying with each specific hour’s percentage of yearly production from 2010, for more information in this see Excel file “Simulation model – Sheet, Electricity demand 2010”and Appendix 22.

𝑃𝑃�� =𝑃𝑃��

𝑃𝑃��∙ 𝑃𝑃��

This means that it is assumed that 2009 is representative in regard to total production from wind turbines, whereas 2010 is assumed representative in regard to the hourly distribution.

14.1.3 Hydro power Since no water based electricity production facilities are placed in Eastern Denmark, all water production is imported from Sweden. The total yearly amount is based on values from 2009 and is determined by subtracting the wind based power production of 14% from the total wind, hydro and solar power production of 18% [48] since there is no solar power production in Eastern Denmark.

Because the hydro power production is imported, it is assumed to be controlled by demand, meaning that it will most likely be imported when demand is high. Therefore the hourly production pattern is modeled by the demand pattern by simply multiplying the hourly demand with the 4 % hydro power production.

14.1.4 Solar energy Solar energy can be applied either for direct electricity production or as thermal energy for either district heating or for direct evaporation of CO2.

Hourly production data is based on a reference year obtained from [47].

14.1.4.1 Power According to Energinet [48] there was no electricity production from the sun in Eastern Denmark in 2009. However as it could potentially play a big part in future scenarios the possibility for implementation has been included.

When implemented, the total yearly contribution is calculated based on a percentage of the total consumption, and then afterwards distributed onto the hours of the year based on a Danish weather reference year [47]

14.1.4.2 Heat Solar heat is not included in the base scenario because the technology is not presently utilized in the Copenhagen district heating system. It could however play a significant role in future energy systems, also in an urban energy system, and therefore the possibility for inclusion has been implemented.


In case it is implemented it is scaled in exactly the same way as the power contribution, which means that only the solar irradiance influences the simulations and not the output temperatures. In real operation the CO2 system would be able to obtain more energy from the same irradiance due to the lower temperatures needed, which would both increase the possible utilization period, increase the overall efficiency due to decreased temperature losses to the surroundings while also decreasing the needed investment costs because cheaper solar arrays can be utilized.

14.1.5 Nuclear Nuclear power is included in the system because it amounted to 7 % of the total consumption of Eastern Denmark in 2009, due to imports from primarily Sweden [48]. This means that even though nuclear plants are thermal production units, it is not assumed to contribute with heat production for the system.

Just as it is the case with the imported hydro power, it is assumed to be imported when demand is high, and is therefore scaled by the hourly consumption.

14.1.6 Geothermal To simplify simulations geothermal energy is assumed hot enough to supply district heating directly, in reality this is not always the case. In Copenhagen for example the temperature out of the ground is 70⁰C, which must then be heated further by an absorption heat pump driven by hot steam from a power plant before it can be used in the district heating network [19].

In actual operation the CO2 system would have an advantage over the H2O system due to the very low temperatures needed, decreasing the needed depth of the system and thereby also the investment costs.

14.1.7 Import/export not taken into account In the base scenario, the energy system is modeled as the actual energy system of Eastern Denmark in 2009, with the previously described assumptions. To make it possible to simulate the system, another assumption is that there are no possibilities for import of electricity. With regard to exports it does not pose a problem because the simulation program will produce the necessary energy with as little as possible fuel inputs, which is always obtained without exports.

14.1.8 Final distribution All of the mentioned technologies work together to meet both electricity and heat demand every hour throughout the year. To minimize the use of fossil fuels the technologies have been prioritized based on their energy consumption. An extensive explanation of how this is done can be found in Appendix 22, however the general priority is;

1. First all available renewable production and import contributions are subtracted from the demand on an hourly basis.

2. Then the CHP is used to its full capacity in two different ways, dependent on the system. a. In the H2O system the CHP plant attempts to meet demand of both electricity and heat by

scaling production, in case additional heat can be produced and there is room in the storage it will be stored for later use.


b. In the CO2 system the CHP plant delivers the needed amount of electricity in condensing mode and then attempts to meet thermal demands by varying the distribution of cooling water between the sea and vapor production for the system.

3. If demand cannot be met by renewable production, imports and CHP production then either boilers for the H2O system, and sea based vapor or liquid production for the CO2 system is utilized.


15 Introduction to the simulation model In the following section a short introduction to inputs for the main simulation model, see excel file “SimulationModel” on the enclosed CD, will be given. The model is constructed in Microsoft Excel and is able to calculate performance results and simulate system behavior based on a variety of inputs. The model is quite extensive making a full explanation unsuitable for the main report, therefore a more comprehensive explanation are located in Appendix 22.

The following section will only describe the first sheet in the model, which is the input sheet that contains all the variables that can be changed in the model. Each of the 29 variables included are based on some assumptions and will influence the simulations and results in different ways and magnitudes, which is why each of them will be briefly explained, both with regard to the actual implementation in the model, as well as the reasoning behind the base scenario value. The base scenario is the first set of simulations conducted, where the idea is to determine the efficiency of the two systems in a situation that as closely as possible resembles the present one. Results of this base scenario is presented in 16.1, and will then afterwards be used as a reference value for a range of alternative simulations.

15.1 Input sheet The purpose of the input sheet is to make it possible to quickly and easily make changes in the inputs for the simulations, in the following section the different parameters are listed as well as a brief introduction to the implementation of each.

15.1.1 Simulated area The simulated area represents the size of the simulated area. Since all calculations are scaled by this number this will not affect how the systems perform, but will merely increase or decrease the total amount of input energy needed. The base scenario simulates 1,000,000 m2.

15.1.2 Ground temperature This function has been included to enable simulation at different ground temperatures however since all cycles must be remodeled in DNA for each temperature change, only 3 temperatures are possible to choose; 3⁰C, 8⁰C and 13⁰C, where 8⁰C is the one used in all instances where nothing else is mentioned.

15.1.3 Thermal losses in district heating distribution The heat losses in the distribution network are an obvious source of inefficiency in the H2O system. The default value of 7 % is a best case scenario [17], meaning that the system is placed in a densely populated city environment with multi storey buildings and well insulated pipes. In case the system is to be placed in a less dense area, this value should be increased accordingly.

In addition, if simulating situations where heat demand are decreased due to increased insulation or other saving measures, this value should also be increased since the amount of heat lost will represent a larger amount of the total energy delivered.


15.1.4 Change in the four thermal demands This input has been included to enable the possibility of adding or subtracting specific thermal demands. The base value is 100 %, representing no change from the constructed case demand patterns. If other values are used then they will simply be multiplied with the hourly demand of the chosen energy service.

15.1.5 Percentage of wind power in system Wind power is one of the major contributors to the Danish energy system and its share is expected to increase in all the future scenarios encountered. In the base scenario this value is set to 14% based on the production distribution of Eastern Denmark in 2009 [48].

This value is used to calculate the total yearly contribution from wind turbines and then distributed on the hours of the year according to the actual production levels of 2010.

15.1.6 Percentage of solar power in system There were no solar power production in Eastern Denmark in 2009, therefore the base value is 0 %. If an amount is included it will be used to determine the total production from solar throughout the year, after which the production will be distributed on the hours of the year based on the solar irradiance for each hour in a Danish reference year [47].

15.1.7 Percentage of electricity imported based on hydro power Eastern Denmark usually imports part of the utilized electricity from primarily Sweden, making the Danish power production distribution dependent on the Swedish one. In the base scenario this leads to 4 % of the Danish electricity being produced by means of hydro power production in Sweden, based on values from 2009 [48].

The contribution from Swedish hydro power production is scaled by hourly consumption, since it is assumed that the power will be imported when demand is high. This is a necessary simplification since the actual hourly import is based on a large number of factors which is not included in this simulation setup.

15.1.8 Percentage of electricity imported based on nuclear power Just as it is the case with the imported hydro power, Eastern Denmark also imports electricity from nuclear plants in primarily Sweden. This contribution was 7 % in 2009, and it is scaled according to hourly demand based on the same assumptions as the imported hydro power. The imported hydro and nuclear power is thereby treated in the same way and could be handled by a simple input, but for illustrative reasons it was chosen to separate them.

15.1.9 Percent change in electricity demand compared to 2010 This value is included to make it possible to include the expected development in electricity consumption in the simulations. The base scenario naturally has this value set to 0 %, but other scenarios will require this option. The implementation of this change is made by adding or subtracting the prescribed amount directly from the hourly electricity demand calculation.

15.1.10 Percent scalable electricity production from non-thermal sources In some areas and scenarios the availability of CHP production might be limited. To enable simulations in these situations this variable is included. It should be noticed that the scalable production is the remaining electricity demand after all other production measures have been utilized, thereby only influencing the


amount of power that must be produced by CHP plants. In the base scenario it is set to 0 %, meaning that all scalable electricity production results in available heat production for the DH system.

15.1.11 Size of hot water storage in CO2 system Two different way of storing energy is included for the CO2 system. In the water based storage solution, it is assumed that a hot water tank just like those presently utilized, can store the power plant cooling water until CO2 vapor is needed in the system. This approach has the obvious advantage that it is simple and a well known technology, whereas the disadvantage is that only heat can be stored, which means that it can only balance the vapor side of the system. In the base scenario this storage is not included because the system balances almost perfectly without it when only considering vapor production.

15.1.12 Size of vapor/liquid buffer in CO2 system The vapor/liquid buffer is the second possible way of including storage in the CO2 system. This solution is assumed to consist of two large pressurized tanks or a larger number of smaller ones, each connected to one of the supply pipes, whereby sudden changes in demand should be absorbed by subtracting from one tank and adding to another, thereby ensuring that the systems overall mass balance remains intact. In the base scenario this value is set to zero because the system has little use for additional balancing measures.

15.1.13 Size of storage in H2O system In the present system, a number of storage tanks are utilized to balance production and demand, thereby limiting the number of hours where boilers must be utilized to cover heat demand due to low electricity demand. In the base scenario, the size of this storage is determined based on the actual size of the storage tanks at Avedøre CHP plant, and calculated in section 14.1.1.3 to be 2.27 hours of full load production. This denomination is used to make the desired storage size scale with the specific demands of the simulated system by multiplying it with the highest heat demand of the year.

The storage will be filled whenever there is a possibility for extra production, either from freely available sources such as solar heat or geothermal, or when the electricity demand is high enough to allow the CHP plant to produce additional heat.

15.1.14 Percent of district heating demand from solar heat The amount of solar heat in the district heating networks has been increasing for a number of years and is expected to increase by 200.000 m2 per year until 2020 [14]. In the base scenario no solar heat is included because there presently is no solar heat in the district heating system of Copenhagen [50]. The likely cause of this is space considerations, in a densely populated area the space consumption of large solar arrays is undesirable compared to recreational areas or buildings. In some future scenarios solar heat might be implemented on roofs or outside the city and transported through longer transmission lines, which is why the possibility is implemented in the simulation model. If implemented the desired percentage of total yearly heat demand is used to determine the total amount to be produced, which is then distributed hourly by solar irradiance in the reference year [47].

15.1.15 Percent of district heating demand from geothermal Geothermal heat production presently account for approximately 1% of the total consumption of Copenhagen [51], which is the value utilized in the base scenario. The amount is distributed as a flat rate contribution in all hours throughout the year, since the production is limited by the heat input from the


ground to the water pumped through the geothermal boreholes and that does not change throughout the year.

15.1.16 Percent of boiler production from heat pumps As mentioned in section 11.1.1 one of the most promising solutions to the problem of lower thermal electricity production leading to decreased possibilities for CHP production is to implement large central heat pumps to utilize the excess electricity production for district heating production [52]. Therefore this is an essential variable to take into account when simulating and comparing possible future energy systems, as explained in section 12.1.1.

It should be noticed that this value only applies to the amount of heat that is produced from boilers since renewable sources, CHP production and storage is all prioritized higher when attempting to meet demand. The input value divides the needed boiler production between heat pumps and boilers to make it possible to vary the degree of implementation. The base scenario value is 0 %, since no heat pumps are currently implemented in the Copenhagen area.

15.1.17 COP of heat pumps When implementing heat pumps a very central information is the assumed COP of the units since this is directly related to the needed electricity input. In the base scenario the overall annual COP is set to 2.8, based on values from Advansor A/S heat pump for district heating in Frederikshavn [23], however it does not affect the results in the base scenario since the implementation of heat pumps is assumed to be 0 %.

15.1.18 Choice of heat pumps in CO2 system - Space Heating This variable makes it possible to change the type of heat pumps utilized for space heating in the CO2 system. When choosing “0” closed loop heat pumps will be utilized, see section 12.6.2.2 for closed loop description, if “1” is chosen open loop heat pumps will be utilized, see section 12.6.2.1 for open loop description. The difference is that the closed loop is more efficient when only relatively low temperature lifts are needed, such as the 40⁰C to 60⁰C lift needed for space heating, whereas the open loop is more efficient when high temperature lifts are needed, such as the one from 8⁰C to 60⁰C needed for domestic hot water production. In the base scenario, the default value is “0”, since the closed loop heat pumps deliver the best overall system performance.

15.1.19 Choice of heat pumps in CO2 system - Domestic Hot Water This has the same function as described above, however it changes the choice of heat pump for the domestic hot water production instead of space heating. In the base scenario, the value is “0”, meaning that the chosen heat pump is not actually the best one for the system, however the resulting increase in coal consumption is less than 0.9%, making the need for two different heat pumps seem unnecessary.

15.1.20 Ambient temperature change This possibility is far from fully implemented, and simply raises the outside temperature, which will decrease the COP of the refrigeration systems in the H2O system accordingly. The actual effects of increasing ambient temperatures are far greater than can be covered adequately in this project, and therefore no simulations have been conducted while changing this parameter.


15.1.21 Building distribution The building distribution plays a very crucial role in the results of the system comparison. For the CO2 system the building distribution determines how well the system can balance supply and consumption, where especially supermarkets play an important role since they are the only consumers of refrigeration. In the H2O system, the building distribution decides the heat demand, and thereby the electricity to district heating demand ratio, which in turn determines the need for boiler based production. The base scenario distribution is based on the actual composition of Copenhagen, with a range of simplifications covered in section 13.1.

15.1.22 Heating value of chosen fuel (LHV) The lower heating value (LHV) of the fuel is implemented primarily to enable the output of the simulation to be given in tons of fuel equivalent. The basic reasoning being that the more easily visualized mountain of fuel, will indicate the energy consumption more clearly than an amount of joules. Changing this value will not affect the systems internal relationship and thereby comparison, but merely makes it possible to base the energy to fuel conversion on other sources. In the base scenario the value is set to “24600 kJ/kg” based on values from [3].

15.2 Results overview There are a couple of ways to easily determine the overall effects of the changes implemented, which is described in the following sections.

15.2.1 Total coal consumption The primary indicator is placed at the bottom of the input sheet, where the total yearly coal consumption of both systems is presented, along with the difference between them in percent. The H2O system is used as the base for the calculation, meaning that if the percentage value is negative, then the coal consumption used to operate the CO2 system is smaller than the H2O systems, whereas a positive value indicates increased consumption from the CO2 system.

15.2.2 Hourly coal consumption If more detailed results are desired, the second sheet in the file, called “CoalPlots”, contains hourly coal consumption values, as well as electricity production and consumption values for both systems.

15.2.3 Balancing capacities If focus is on how the systems cope with the implemented changes on a functional level, then the third sheet, called “BalancingPlots”, contains two sets of plots that illustrate how the primary balancing capacity of each system functions on an hourly level, followed by the remaining demand after all primary balancing capacity has been utilized. This remaining demand is the amount of production that is handled by peak production plants, which is less efficient and therefore undesired from an efficiency point of view.

This is useful when attempting to determine how well the systems cope with the implemented changes and if additional balancing measures might be needed to balance the system.


16 Results In the following sections a range of different results will be presented, each of them based on a variety of different assumptions about the energy system into which the CO2 system is implemented. This is done to attempt to take the complexity of the energy system into account and additionally indicate the importance of different circumstances on the overall usability of the system. The idea is to attempt to implement some of the likely changes in the future energy system to clarify if they have positive or negative effects on the desirability of the CO2 system.

Since both systems deliver the exact same energy output, the amount of coal input is a direct measure of the efficiency of the system, which is why it will be used to compare the two systems. In addition the resulting CO2 emissions are directly dependent on the coal consumption since 95 kg CO2 is emitted per GJ coal consumed [3].

Initially the results of the base scenario will be presented. This illustrates implementation into the current energy system, and will afterwards be used for comparison with the results obtained from the more specialized scenarios to achieve a simple indication of the effects of the different changes.

16.1 Base scenario In the base scenario the assumptions are made to in order to resemble the current energy system as closely as possible within the restrains of the needed simplifications. This means that the energy production facilities are exactly as explained in section 0.

16.1.1 System performance Figure 36 below illustrates the performance of each of the systems with regard to balancing consumption and production throughout the year. The top graph shows how the H2O system scales thermal production from the power plant to meet demand, as well as the storage level for each hour. The middle graph shows the percentage of possible vapor production that is utilized in the CO2 system, and the bottom graph illustrates the production levels needed to meet the remaining demand after the production scaling and storage capacity has been fully utilized for both systems, thereby indicating the production from boilers for the H2O system and the sea for the CO2 system.


Figure 36: Thermal production need in excess of CHP production for each system, including storage level in H2O system

It is obvious that even with storage capacity the H2O system has a much greater need for additional thermal production during the winter. In this base scenario, 9% of the total heat production in the H2O system is based on boilers because the electricity demand is insufficient to allow for adequate heat supply. In actuality the average value for Denmark is much higher; in 2009 22.8% of the district heating in Denmark was produced without electricity [3]. The reason for this discrepancy between the 9% and the 22.8% is that the 22.8% is an average of the total Danish production of district heating and varies a lot dependent on the local environment. In the Copenhagen district heating network there are 4 different CHP plants and in addition 3 waste incineration plants [50] leading to a situation where much of the electricity for the entire eastern region is produced there, resulting in very good possibilities for heat production. For the Copenhagen area, the amount of district heating produced without electricity in 2010 was 10.4%, indicating that the base scenario closely resembles reality in that regard.


The CO2 system seems to have a good coherence between production and consumption, as the remaining thermal demand after initial balancing measures is small with mostly need for sea based liquid production during the summer.

With regard to the coal consumption the yearly consumption pattern is illustrated in Figure 37 below.

Figure 37: Hourly coal consumption for each system

It is clear that the consumption of the two systems is relatively similar throughout the year, with the existing H2O system having a slight advantage during the winter when the heat demand is highest, whereas the CO2 system has a slightly lower consumption during the summer where the synergy effect ensures that the increased demand for refrigeration does not impact the system to the same extend as in the H2O case.

The final results can be summed up by the yearly total coal consumption of each of the systems, which has been done in Table 25 below.

Yearly total coal consumption [ton] [%]

H2O 27131 Base CO2 29292 8.0%

Table 25: Total yearly coal consumption of each system

Overall, the CO2 system performs 8% worse than the H2O system. The reason behind this result is that the CHP plant has to deliver an increased electrical output as the CO2 system requires additional electricity for the heat pumps. Excess heat from the full condensing mode operation is more than enough to produce the needed vapor at almost all times, but the additional need for electricity is greater than the increase in the plants electrical efficiency resulting from condensing operation.

A simple comparison can be made with regards to the efficiency of heat production, if the CO2 system is required to deliver the same amount of power and heat as the H2O system in full back pressure operation, then the amount of primary fuel input can be calculated, which is done in Table 26 below.


Heat

required COP

assumed

Power for heat

production

Power to be produced

Plant electrical efficiency

Fuel input needed

[MJ/s] [-] [MW] [MW] [%] [MJ/s] H2O 330 - 0 215 36 595 CO2 330 5 330/5 = 66 215+66 = 281 42 281/0.42 = 669

Table 26: Calculation of fuel input needed for the CO2 system to produce the same output as the H2O system.

In the presented calculation the best case scenario COP of 5 is assumed, see section 12.6.2.1.3, and still the CO2 system requires 12.5% additional fuel input to deliver the same outputs. This is however not surprising since the comparison is made in the best possible scenario for the H2O system; no cooling is included and the heat production is managed by solely by a CHP plant, meaning without boilers. When comparing the 12.5% increase in fuel input with the simulation results of 8%, it is obvious that there are also parts of the energy system where the CO2 system is more efficient.

It is however clear from the results that the current H2O based system is highly efficient when considering the current demands and energy system. The conclusion is that with the existing energy system, the CO2 system would not improve the overall energy efficiency, mainly because such a large part of the Danish electricity production currently leads to easy possibilities for utilization of the low quality heat.

16.1.2 Primary fuel costs A brief investigation of the primary fuel cost of operating the two energy systems annually will be carried out. This is meant to serve as an economical estimate of operating the two systems annually, rather than inputs to advanced economical calculations, because many economical factors are unknown in proposed CO2 system.

The primary fuel costs are in this assessment expressed as a monthly spot market price of coal, multiplied with the coal consumption in each hour of the respective months. It is assumed that the primary fuel costs are from the plant’s point of view and that all the taxes related to coal are subjected on to the consumers. Coal spot market prices from 2009 [53], see Excel file “Spot market coal prices” can be seen in Table 27.

Coal spot market prices 2009 - January 434.3 DKK/ton 2009 - February 411.6 DKK/ton 2009 - March 329.0 DKK/ton 2009 - April 349.7 DKK/ton 2009 - May 313.2 DKK/ton 2009 - June 322.3 DKK/ton 2009 - Juli 324.7 DKK/ton 2009 - August 333.2 DKK/ton 2009 - September 309.2 DKK/ton 2009 - October 327.6 DKK/ton 2009 - November 335.2 DKK/ton 2009 - December 370.0 DKK/ton

Table 27: Coal spot market prices in 2009

The results of annual primary fuel cost of both energy systems can be seen in Table 28.


Yearly primary fuel costs

[DKK]

H2O 9581173

CO2 10368657 Table 28: Operation cost of both energy systems

The results shows, not surprisingly, that the CO2 system is more expensive to operate than the H2O system since the primary fuel costs only depends on the fuel input in this assessment. Operating the H2O system would save approximately 0.78 mill. DKK on coal compared to the CO2 system, for the simulated 2.75% of the Copenhagen area.

16.1.3 CO2 emissions An investigation of the CO2 emissions related to operating the systems has been carried out. As with the primary fuel costs, the purpose of the investigation is to provide an estimate of the emissions, which can be used get an idea of the quantity. The CO2 emissions are assumed to only relate to the amount of primary fuel burned and that CO2 emissions from the system do not come from other sources than the CHP plant and boilers. Additionally it is assumed that no carbon capture storage (CCS) is included at the CHP plant.

Calculation CO2 emissions are made by multiplying the coal burned throughout the year, with the mass of CO2 emitted from burning coal. The mass of CO2 emitted from burning coal is calculated to be 2263 kg/ton according to [3]. The total CO2 emitted from operating the energy systems can be seen in Table 29 below.

Yearly CO2 emissions [ton]

H2O 61398

CO2 66288 Table 29: Yearly CO2 emissions from operating both energy systems

It can be noted that operating the H2O systems would save 4890 tons of CO2 every year, compared to operating the CO2 system.

16.2 Storage in CO2 system Storage has been implemented in the H2O system in the base scenario because it is a part of the present system, but storage in the CO2 system is instead implemented in this separate sensitivity analysis. This is done in order to investigate the effects on primary fuel consumption when introducing one of the two possible storage solutions in the CO2 system.

Storage is added to the simulation model by means of either a hot water storage as found in the H2O system or a liquid/vapor buffer. The liquid/vapor buffer works as described in section 15.1.12, and the way it interacts with the simulation model is explained in Appendix 22.

In order to investigate the impact on primary fuel consumption, the capacity of the storage, represented by the number of full load hours, is varied from 0 hours in the base scenario up to 10 hours in steps of 1 hour. The result of this sensitivity analysis can be seen in Figure 38 below.


Figure 38: Coal consumption in the CO2 system by implementing storage capacity

As the graph clearly shows, adding storage to the CO2 system in the base scenario have almost no effect on system performance. The change is only around 200kg of primary fuel input by having the hot water storage and insignificant 20 ton by having a liquid/vapor buffer.

In regards to the hot water storage the reason it has no impact on the system performance is because hot water storage is only able to supply heat for vapor production and the CO2 system has almost no need for extra vapor production after initial balancing measures from freely available energy sources, which also can be seen in Figure 36.

Having a liquid/vapor CO2 buffer also shows no real impact on system performance, and with regards to the vapor CO2 the reasons are the same as with the hot water storage – no vapor production is needed in the system. Liquid CO2 is used as balancing measure but only to a limited extent during the summer where there is a need for additional cooling. The storage covers the entire demand for extra liquid production, thus replacing sea based production as seen in Figure 39. However, liquid production from the sea is produced with an average COP close to 11, meaning that the primary fuel saved by delivering liquid from storage instead of sea based production is minimized.

Figure 39: Liquid storage balancing the CO2 system

Introducing storage in the CO2 system is not beneficial from a cost benefit point of view as the system is highly efficient when balancing production and consumption with available heat and cold sources.

16.3 Distribution between building usage Distribution between building use in the base scenario has been identified based on numbers from [44] and [45], but the same distribution is not necessarily found in all areas in Copenhagen or in other cities. This


section carries out a sensitivity analysis to investigate the influence on system performances with different building compositions in the energy system. 4 different compositions other than the base scenario are made along with extreme cases with only one consumer type.

Changing the building composition has a direct influence on the distribution of the demand for thermal energy services and thus the electricity needed and the primary fuel input to cover it. Figure 40 below illustrates the building distribution in the base scenario for comparative reasons.

Yearly total coal consumption [ton] [%] H2O 27131 Base CO2 29292 8.0%

Figure 40: Building distribution and yearly coal consumption base scenario

16.3.1 Less office, increased supermarkets The first sensitivity analysis made, is where 6% of the office buildings has been replaced by supermarkets, which in effect increases the need for cooling and decreases the demand for heating. Results can be seen in Figure 41, where the relatively small change in building distribution makes the CO2 system perform 6.5% better than base scenario situation and only 1.5% worse compared the H2O system. The H2O system uses a bit more coal compared to the base scenario, because of the increased cooling demand. Producing one unit of cooling in the H2O system, is in an overall perspective more inefficient than producing one unit of heating, as cooling has to be produced by decentral systems using electricity.

Introducing more cooling demand to the system additionally increases the impact of the synergy effect in the CO2 system, which helps to balance the system and thereby reduce primary fuel input to the CHP plant.


Figure 41: Distribution between building usage and results – less office and more supermarkets

16.3.2 Less office, increased residential and supermarkets The next sensitivity analysis made, drastically reduces office buildings and instead introduce more supermarket and residential. The office building area is reduced by 23% and supermarkets and residential building areas are increased by 5% and 18% respectively. The idea behind this change is to attempt to resemble a city area primary used for apartment complexes and with only few offices buildings.


Results can be seen in Figure 42, and show only a small reduction in primary fuel consumption for the CO2 system, still the system improves 6.2% in the comparison with the H2O system in the base scenario. The reason is that the large increase in heat demand from residential combined with the increased cooling demand from the supermarkets, forces the CHP plant in the H2O system to cover both extra electricity for cooling and extra heat demand, which leads to an increased number of hours where inefficient boilers have to be operated to cover the demand for heat because the CHP plant is unable to do so.


Figure 42: Distribution between building usage and results – less office and more residential and supermarket

16.3.3 Less mall, increase supermarket and residential This sensitivity analysis reduces supermarket area by 2% and removes the mall. Instead the residential building area has been increased by 3%. The idea is to see how much the supermarket and mall building are influences the overall performance of the energy systems. Results of the sensitivity analysis can be seen in Figure 43, and shows almost unchanged primary fuel consumption in the H2O system, and a small increase in CO2 system. The CO2 systems extra fuel consumption when compared to the H2O system in the base scenario increases by an additional 2.1 % from only a change of few percent in the building distribution, which is not that surprising. With only little cooling demand the synergy effect becomes insignificant, and the CO2 system cannot compete with the COP of the heat production from the CHP plant, which is much higher than the one obtained with decentral heat pumps in the CO2 system.


Figure 43: Distribution between building usage and results – less residential and more office, mall and supermarket

16.3.4 Ørestaden This sensitivity analysis is based on the building distribution of Ørestad according to [54], where as much as 60% of the building distribution is office buildings, 20% is residential and 20% commercial buildings. In this analysis the commercial buildings are distributed as 15% mall and 5% supermarket as the largest shopping mall in Denmark, Fields, is located in Ørestad.


Results can be seen in Figure 44, which shows an improvement of 4% in the CO2 system compared to the H2O system, which is likely due to the increase in cooling demand, mainly comfort cooling, and a reduction of heat demand from the residential sector. The improvement could have been even better if more supermarkets with refrigeration demand was included, as the increase of comfort cooling does not require much extra liquid CO2 to provide and do not affect the synergy effect much. Overall the consumption of primary fuel is decreased notably, which is likely due to the heavy reduction in the residential sector with a high heat demand throughout the year.


Figure 44: Distribution between building usage and results – Ørestad

16.3.5 Only a single consumer type The last sensitivity analysis is to investigate the “extreme” cases where the systems are to supply only one consumer type, meaning 100% building distribution of each consumer type.

Results can be seen in Table 30 below, where the influence of each consumer type is clearly visible in regards to system performance. The most remarkable is to see the results in the supermarket case, where the CO2 system performs 53.6% better than the H2O systems. The reason for this is a very significant synergy effect within the supermarket itself, where vapor production from refrigeration and comfort cooling is used to produce domestic hot water and space heating which again supplies the cooling units. In Figure 45, the balancing demands other those from the CHP plant is shown, where the CO2 system at almost all times requires sea based production, mainly liquid. The CO2 system is however able to produce liquid with a COP between 9.76 - 12.32, see section 0, whereas the H2O system just have to use more electricity to produce the same amount of cooling. It is clear that the CO2 system is preferable in the supermarket case, but one must also consider the amount of sea water needed to produce liquid CO2, which is quite high.


Only Supermarket Only Mall Yearly total coal consumption Yearly total coal consumption

[ton] [%] [ton] [%] H2O 27837 Base H2O 24455 Base CO2 12912 -53.6% CO2 23846 -2.5%

Only Residential Only Office Yearly total coal consumption Yearly total coal consumption

[ton] [%] [ton] [%] H2O 29919 Base H2O 24455 Base CO2 32680 9.2% CO2 26366 7.8%

Table 30: Extreme cases with 100% building distribution of each consumer type

Figure 45: Remaining thermal demand after balancing measures in 100% supermarket case

To sum up the sensitivity analysis, it is clear that the building distribution has a large impact on the performance of the systems. Heating demand surpasses the cooling demand by far in the consumption pattern in the base scenario, and this benefits the H2O systems as district heating can be produced with a much higher COP than the heat pumps in the CO2 systems. The great difference between heating and cooling demand also reduces the synergy effect in the CO2 system, and thereby diminishes one of the main advantages. If an energy system has the same thermal demands as a supermarket, and to some extent a mall, it is shown that the CO2 system would be superior to the H2O systems in regards to primary fuel use.


16.4 Variations in ground temperature When simulating the systems performance, the ground temperature is assumed to be 8⁰C constantly because that is the average in Denmark [12]. This might however vary during the year, which makes it interesting to see how a change of the ground temperature affects the systems performance.

When changing the ground temperature, the pressure in both pipes must be changed accordingly to avoid unintended condensation or evaporation, resulting in the following three situations being investigated.

Low temperature

Base scenario

High temperature

Ground temperature [⁰C] 3 8 13 CO2 vapor pressure [bar] 35 40 46 CO2 liquid pressure [bar] 40 45 51

Table 31: State points used for sensitivity analysis of the ground temperatures influence on systems performance.

For each situation, the DNA simulation files are utilized to determine new efficiencies for all the cycles connected to the CO2 network with the new temperatures and pressures, resulting in new COP values presented in Table 32 below.

Ground temperature 3⁰C 8⁰C 13⁰C COP Specific

CO2 use COP Specific

CO2 use COP Specific

CO2 use [-] [g/kJ] [-] [g/kJ] [-] [g/kJ] DHW - Open Loop 4.9 3.63 5.0 3.88 5.4 4.13 DHW - Closed Loop 4.1 3.25 4.3 3.50 5.0 4.00 SH - Open Loop 3.0 2.75 3.0 3.25 3.3 3.50 SH - Closed Loop 3.5 3.00 3.7 3.38 4.2 3.75 Comfort Cooling 0.0 4.38 0.0 4.75 0.0 5.38 Refrigeration 6.2 4.25 4.8 4.50 3.7 4.88 Liquid Production, Sea temperature 8⁰C 10.0 4.55 12.3 4.61 20.8 4.93 Liquid Production, Sea temperature 12⁰C 8.4 4.36 9.8 4.50 14.0 4.85 Vapor Production, Sea temperature 8⁰C 60.3 4.37 33.4 4.61 11.0 5.58 Vapor Production, Sea temperature 12⁰C 128.9 4.37 94.8 4.69 11.4 5.58

Table 32: COP and specific CO2 usage values for the CO2 network at different average ground temperatures.

Naturally the COP for heating cycles increase with increasing ground temperatures while the cooling cycles react oppositely. With regard to the specific CO2 use of the cycles then it always increases with increasing temperatures, which is caused by the fact that the lower the temperature of the CO2 is, the greater the enthalpy difference between liquid and vapor phases becomes as illustrated in Table 33 below.


Ground temperature 3⁰C 8⁰C 13⁰C hvap [kJ/kg] 435.9 432.8 427.2

hliq [kJ/kg] 207.1 219.9 233.4

Δh [kJ/kg] 228.8 212.9 193.8 Table 33: CO2 enthalpy values for the two state points at different ground temperatures.

The effect of this change is easily visualized in Figure 46 below, where the needed amount of sea based balancing needed increases with the ground temperature.

Figure 46: Amount of sea based balancing needed at 3⁰C, 8⁰C and 13⁰C ground temperature.

Fortunately the specific CO2 output of the balancing measures increase accordingly, meaning that the larger CO2 demand on a weight base, actually leads to a decrease in electricity consumption for the balancing production. When considering the final results of the simulations, presented in Table 35 below, then the electricity saved on the balancing production actually play a significant role, since the changes in electricity


consumption for consumer thermal production is balanced because of the opposite changes in COP for heating and cooling cycles respectively. This is illustrated in Table 34 below.

Ground temperature [°C] 3.0 8.0 13.0 Electricity demand for thermal cycles [%] 103% 100% 95% Electricity demand for system balancing [%] 125% 100% 81%

Table 34: Development in the two types of electricity consumption in the CO2 system for different ground temperatures.

Ground temperature [°C] 3.0 8.0 13.0 H2O system coal consumption [ton] 27131 27131 27131 CO2 system coal consumption [ton] 29568 29292 28814 Percent difference between CO2 and H2O system [%] 9.0% 8.0% 6.2% Percent difference to the CO2 system at 8⁰C [%] 0.9% 0.0% -1.6%

Table 35: Coal consumption values for different ground temperatures.

It is obvious that temperature increases or decreases of 5 degrees do not impact the overall system performance severely, and will not compose a significant problem to the comparison of the energy systems.

16.5 Solar power scenario Solar power is a technology where solar energy is converted into electricity, without any thermal energy production. The coverage of electricity consumption from solar power is presently very limited in Denmark and non-existing in the energy system in Eastern Denmark in 2009[55]. Rapid development of the solar power technology has led to increased efficiency of the solar cells and decreasing production costs [56] which makes the technology promising in regards to the future electricity production. According to [15] solar power is predicted to cover 9-10% of the total electricity consumption in 2050, which makes the technology impossible to ignore in a future energy system. Thus, a sensitivity analysis is carried out, where solar power is implemented in the base scenario to see the effects on both energy systems.

Solar power is implemented in the base scenario by increasing the percentage of yearly electricity production from solar power without changing any other parameters. The available solar power is varied in steps between 0% to a more extreme case of 50%, even though that is much more than the predicted 10% in 2050. The reason to include more than 10% is to show where the break-even point would be between the CO2 and H2O systems in regards to the coal consumption. An illustration of the effect of implementing solar power can be seen in Figure 47 below.


Figure 47: CO2 systems coal consumption compared to the H2O systems as function of % solar power implemented

The figure shows that up to 10 % solar power there is no real improvement in the relation between the systems, as the extra solar power benefits both systems. However with more than 10% solar power, the CO2 system begins to gain an advantage due to the decrease of electricity and power production from the CHP plant. The H2O system still requires heat production and the extra power production forces the system into running boilers to cover the demand for heat, as the CHP plant otherwise would overproduce electricity. As seen, it requires around 41% solar power before the CO2 system performs as well as the H2O system if no other parameters are changed. Introducing solar power into the energy systems saves plenty of primary fuels in both systems but the influence on the system comparison only favors the CO2 system slightly at the 10% electricity coverage expected in 2050. When the coverage is put to an annual coverage percentage, and the production is rather low in all the other seasons except summer, the power production from the sun will consequently be high during the summer in order to reach the percentage. The CO2 system however uses much less electricity during the summer, as the heat demand is low, leading to a misbalance between production and demand which diminish the benefits of introducing solar power in regards to the CO2 system.

16.6 Solar heating Solar heating is becoming an increasingly popular technology in Denmark both in relation to decentral heating and in relation with district heating. There are several reasons for this, the primary one being that solar heating has proved economical competitive regarding heat production compared to most other energy sources. This is especially true for large solar heating plants, as the marginal heat production price is 2 times lower than medium size plants and 4-6 times lower than small size plants [57]. Additionally by investing in solar heating, the marginal production price of heat is fixed as solar energy is considered “free”, which make the heat prices much more transparent for customers and heat plants. Production also becomes independent of price fluctuation on primary fuels such as oil and gas which is desirable today, as the majority of reserves are located in unstable regions such as Russia (Gas) and the Middle East (oil).


The increasing interest in solar heating in Denmark is reflected in the area of solar panels already laid down for district heating and the area projected in the future. Areas of existing and projected solar heating plants from [14] can be seen in Table 36 below:

Area of solar collectors in Denmark Year Unit Comment

1990 - 2009 90,000 m2 2010 44,000 m2 5 plants 2011 162,000 m2 14 plants projected

Table 36: Area of solar panels in Denmark – existing and projected

According to the projection in [14] another 2 million m2 of solar collectors will be put into operation by 2020, which corresponds to 200,000 m2 a year. The goal is to reach 30% coverage of heat consumption by solar heating in 2030 in Denmark. [15]

16.6.1 Effects of implementing solar heating Solar heating has been implemented in the simulation model, and the percentage of heat demand coverage has been varied in the base scenario to see the impact on the system performances and the coal consumption. Steps from 5% up to 50% heat production from solar have been carried out. The results are shown in Figure 48 below.

Figure 48: Impact on coal consumption when introducing solar heating to the energy systems


From the top graph in Figure 48 it is clear that all the H2O system gradually improve compared to the CO2 system, when introducing more and more solar heating into the base scenario. The bottom graph shows the yearly coal consumption, and as the H2O systems reduce the overall coal consumption, the CO2 system has the same coal consumption no matter how much solar heating is implemented. To be precise only 23kg of primary fuel is saved from increasing the percentage of solar heating from 0 % to 50 % The reason for this is that the CO2 system in the base scenario is balancing heat production and demand very well with just the excess heat from the CHP plant, thereby almost eliminating needs for extra heat production. See Figure 36.

As seen in Figure 36, before introducing solar heating there were only few small spikes, mainly in the winter time, where the excess heat from the CHP is not enough to cover heat demand, and at these times the solar heating can be used as heat source. However during winter, the sun does not shine that often, and heat production in the times with spikes has been insignificant. Excess heat from CHP and solar heating are both considered “free”, meaning they have equal priority in covering the heat demand. Solar heating improves the H2O system slightly as the solar heating can cover some of the heat demand in other seasons than the summer months, where it is needed because the CHP plant runs in full back pressure mode. Improvement of the H2O system performances could have been better, but due to the displacement between production and demand this is not the case.

16.7 Geothermal Heat from geothermal sources has yet to have its impact on the Danish district heating sector, as presently only 1-2% of the heat delivered is covered by geothermal, but in the long term it is predicted that geothermal heat can cover 20-30% of the district heating [19]. A combination of an unfit geological underground in Denmark with regard to thermal heat sources and the fact that reaching feasible temperatures for district heating requires boreholes several kilometers deep, has slowed the integration of geothermal heating.

In the CO2 system geothermal becomes a much more interesting opportunity as all temperatures levels about 8°C can be utilized to produce vapor and thereby available heat. This would lead to less deep boreholes reducing the costs of utilizing geothermal, and would also increase in the number of suitable locations in Denmark.

Geothermal heating is included in the simulation model by a percentage of the heat production for every hour during the year. The way geothermal heating is implemented means that the temperature level is not considered, and the extra electricity used for pumps in the CO2 system and the booster heat pumps in the H2O system are therefore not included. Geothermal is implemented in the simulation model by introducing more and more available geothermal heating in steps from the base scenario, 1%, up to 50% in order analyze the impact on the energy systems. Results of the sensitivity analysis are illustrated in Figure 49, where the coal consumptions of both systems are shown.


Figure 49: Impact on coal consumption when introducing geothermal to the energy systems

It is clear from the graphs that the H2O system benefits from having increased the geothermal heat available, whereas the CO2 system remains unchanged. Benefits in the H2O system are due to the availability of geothermal heating even during the winter, thereby replacing operation of boilers to cover demand, which saves primary fuel. The reasons why the coal consumption in the CO2 system is unchanged are the same as explained in the sensitivity analysis with solar heating, where there is simply almost no need for heat production other than the excess heat from the CHP plant.

16.8 Electricity produced from non-thermal sources

16.8.1 Base scenario As mentioned in section 16.1 boilers play a much smaller role in the fulfillment of district heating demand in Copenhagen compared to the average of the entire country. This is caused by the fact that a very large part of the electricity production for the entire eastern region is concentrated around the city, ensuring high availability of heat from CHP production. This in turn leads to areas where all the electricity is received via the transmission grid, and no local production takes place. In this case all heat production will be based on burning of various fuels directly for heat production.


To investigate how the two systems will compare under such circumstances, a scenario is constructed where all electricity is assumed imported or produced by non-thermal sources such as wind turbines or photovoltaic panels, resulting in a system where there are no excess heat for the district heating network.

The result is a situation where the efficiency of the remaining production possibilities becomes very important. In Figure 50 below the yearly secondary balancing capacities of the two systems are illustrated, where it is obvious that the lack of heat from CHP production not only has a very pronounced effect on the amount of additional production necessary, but also on the number of production hours since the scalability of the CHP heat output were previously ensuring, that the secondary balancing measures were used as little as possible.

Figure 50: Balancing capabilities of the two systems when no CHP heat is available.

When considering the need for additional heat production, the CO2 system obviously has a lower demand, primarily because the production of refrigeration and comfort cooling supplies part of the energy for the system and secondly because the figure only illustrates CO2 vapor and not actual heat, meaning that the electricity used in the final heat production is not included.

In addition to the amount of energy needed, it should be considered how that energy is obtained. The H2O system is based on high temperature heat which, in the present system, must be created with the use of fuel in boilers if excess heat is not present from another process. The efficiency of this transformation is assumed to happen with an efficiency of 95%, which means that almost all the fuel is turned into heat. In the CO2 system the network can be balanced by any available source, with increasing efficiency for higher temperature differences between the source and the CO2. This makes it possible to use a far greater number of sources, for example the air, ground, sewage, sun or, as is the case in the simulations, the sea.

The ability to use readily available sources means that the CO2 system is highly efficient when balancing production and consumption. When considering the simulated sea based vapor production the average yearly COP is approximately 51, while the average COP for sea based liquid production is close to 11, which with 100 % non thermal electricity production results in an overall COP of 48 for the sea based balancing measures because the primary demand is vapor production.

To determine the actual impact of non-thermal electricity production on the systems overall performance, simulations have been performed while varying the distribution between CHP and non thermal production in the range from 0 % to 100 %. The results are illustrated in Figure 51 and Table 37Table 37 below.


It should be noticed that the energy needed for electricity production is still included in the results and represented as coal, even if it is assumed imported or produced from renewable sources. This approach has been chosen because otherwise the results would not illustrate the systems overall energy consumption and thereby efficiency correctly.

Figure 51: Yearly coal consumption for each system, based on the amount of non thermal electricity in the system.

Yearly total coal consumption dependent on percentage of non thermal electricity Percent imported electricity [%] 0 20 40 60 80 100 H2O coal consumption [ton] 27131 28320 29890 31844 34208 36572 CO2 coal consumption [ton] 29292 29294 29302 29330 29378 29435 CO2 percent of H2O consumption [%] 8.0% 3.4% -2.0% -7.9% -14.1% -19.5%

Table 37: Yearly coal consumption for each system, based on the amount of non thermal electricity in the system

It is obvious that as the percentage of non thermal electricity increases the H2O systems overall system efficiency drops dramatically, since the most efficient heat source becomes unavailable. The CO2 system on the other hand shows almost no decline in efficiency, even when there is no excess heat available, the systems overall coal consumption only increases by 313 tons, which is equal to just about 1 % of the initial consumption.

Clearly the highly efficient sea based production ensures that the origin of the electricity used and availability of high temperature sources is of almost no consequence for the CO2 system, while the H2O system suffers an overall increase in coal consumption of 9813 ton, equaling a 35 % increase. The end result is that at 32 % non-thermal electricity production the two systems are equal, where after the CO2 system becomes increasingly more efficient as the percentage of non-thermal electricity is increased further, ending at a 19.3 % advantage over the H2O system.

16.8.2 Heat pump scenario In the future energy system heat pumps are predicted to play a large part in the production of district heating in situations where electricity production does not ensure adequate heat production from CHP plants. To assess how the systems would compare with increasing amounts of heat pumps available to the H2O system, another set of simulations are conducted with the amount of non-thermal electricity production set to 100 % while varying the amount of heat production from heat pumps from 0 % to 100 %. The results are illustrated in Figure 52 and Table 38 below.


Figure 52: Yearly coal consumption for each system with 100% non-thermal electricity production and varying amounts of heat pumps in the H2O system.

Yearly total coal consumption dependent on percentage of non thermal electricity Percent of heat from heat pumps [%] 0 20 40 60 80 100 H2O coal consumption [ton] 36572 36048 35523 34998 34473 33948 CO2 coal consumption [ton] 29435 29435 29435 29435 29435 29435 CO2 percent of H2O consumption [%] -19.5% -18.3% -17.1% -15.9% -14.6% -13.3%

Table 38: Yearly coal consumption for each system with 100% non-thermal electricity production and varying amounts of heat pumps in the H2O system.

The results clearly indicate that even with the entire heat supply based on heat pumps, the H2O system cannot reach the efficiency of the CO2 system. The fact that part of the heating is supplied from refrigeration and comfort cooling production, in combination with easy access to additional energy from the surroundings ensures that the CO2 system performs far better in situations where no high temperature excess heat is available.

The numbers presented here for the H2O system are based on values from an installed heat pump system in Frederikshavn [23], which is based on using sewage water as a heat source leading to a relatively high COP of 2.8. To assess how different COP values will impact the results another set of simulations were conducted with both non-thermal electricity production and amount of heat pumps set to 100 %, while varying the COP of the heat pumps in the H2O system. The results are illustrated in Figure 53 and Table 39 below.


Figure 53: Yearly coal consumption for each system with 100% non-thermal electricity production and heat pumps in the H2O system, while varying the COP.

Yearly total coal consumption dependent on percentage of non thermal electricity COP of heat pumps [%] 2 2.5 3 3.5 4 4.5 5 H2O coal consumption [ton] 38361 35272 33213 31742 30639 29781 29095 CO2 coal consumption [ton] 29435 29435 29435 29435 29435 29435 29435 CO2 percent of H2O consumption [%] -23.3% -16.5% -11.4% -7.3% -3.9% -1.2% 1.2%

Table 39: Yearly coal consumption for each system with 100% non-thermal electricity production and heat pumps in the H2O system, while varying the COP

From the results it is obvious that the COP of the heat pumps in the H2O system has to be very high if the system is to surpass the CO2 system. As mentioned the existing system in Frederikshavn, which is based on sewage water has a COP of 2.8, which is very far from the 4.7 that is necessary.

Based on the conducted simulations, it is obvious that in situations where there is no high temperature excess heat available, the CO2 system clearly outperforms the existing system, even if heat pumps are assumed to handle the heat production instead of boilers.

16.9 2050 scenario The CO2 system is presently at a very early stage of development, and if the system were to become commercially ready it would be many years into the future from now. At that time the energy system would be different from today, as the trends moves towards an increased share of renewables and a goal of having a fossil free energy sector in 2050 [15]. Thus, it would only be logical to compare the energy systems in a 2050 scenario where predictions of the electricity and heat production composition, as well as energy savings, would be used as inputs for the simulation model.

The references used to create the 2050 scenario are a combination of [15] and [14], as these provide numbers of predicted shares of energy sources related electricity and heat production, and includes energy savings as well. Other report presenting a 2050 scenario such as [58][59] and [9][60] has also been assessed. However, the 4 different scenarios presented in [58] and the one presented in [59] provides


insufficient information regarding energy savings and what energy sector each energy resource is related to, which is crucial information as the transport sector is excluded from this study.

The scenario presented in [9] and in the background material [60], did however provide sufficient information to create a scenario, but predictions are very similar to the ones made in [15] and [14], thus it is chosen to simulate a mix of IDA Klimaplan 2050 and Varmeplan Danmark which is a joint effort between Rambøll and Aalborg University.

16.9.1 IDA klimaplan 2050 and Varmeplan Danmark 2010 Predicted electricity and heat production composition in 2050 in Denmark is from [15] and [14]. An overview of the predicted energy system in 2050 is shown in Figure 54, where the energy sources are presented on the left side and the consumption on the right.

Figure 54: Overview of predicted energy system in 2050, [15]


Based on Figure 54 and other predictions from [15] and [14] Table 40 below has been created, however to be able to create simulation model inputs several assumptions has been made;

• It has been assumed that the 5% wave power will be included as wind power in the model, since wave power production will most likely occur when the wind is blowing (neglecting influence of water streams).

• 1% from synthetic fuel will instead be included as biomass/biogas in the model. • Biomass boilers and CHP (Various fuels) are not included as direct inputs, because the simulation

model itself identifies the coverage from CHP and boilers, as boilers are running when the electricity/heat ratio of consumption is below the full backpressure ratio of the CHP plant.

• The lower heating value (LHV) of biomass is put to 18500kJ/kg as it is a realistic average value according to Excel file “Heat content various biomass types”

• The large heat pump input to the model has been put to 80%, as it is the percentage of the boiler production covered by heat pumps. Combined are the biomass boilers and large heat pumps covering 10% of the heat consumption and 8% of this is large heat pumps. An annual average COP of 2.8 is used in the model, which is based on Advansor’s large heat pump in Frederikhavn utilizing sewage water as heat source. [23]

• The total heat demands (domestic hot water and space heating) will be reduced by 50% according to [14].

• Heat loss from the district heating network is in Figure 54 stated as 21%, however this is the country average and 7%, representing a densely populated area such as Copenhagen, is still assumed to be model input.

Electricity production composition Heat production composition Coverage Unit Coverage Unit

Solar Power 9-10 % Solar Heating 6-7 % Wind Power 60-65 % Geothermal 4 % Biomass/Biogas 22 % Biomass boilers 1-2 % Synthetic fuel 1 % Large heat pumps 7-8 % Wave Power 5 % CHP (Various fuels) 79-81 %

Model inputs Model Inputs Solar Power 10 % Solar Heating 7 % Wind Power 67 % Geothermal 4 % Biomass LHV 18500 kJ/kg Large heat pumps 80 % Heat pump COP 2.8 Reduction in heat demand 50 %

Table 40: Electricity and heat production composition and inputs to simulation model

Figure 55 below illustrates on the two top graphs the balancing production and consumption of the CO2 system and the H2O system throughout the year. Utilization of the CHP heat production in both systems shows not surprisingly a very fluctuating behavior, as a result of a large increase in share of wind power and solar energy. The H2O system has a higher degree of utilization than the CO2 system, but also forces the CHP plant to ramp up and down quickly, as 0% and 100% utilization can occur within a very short period of time. These sudden spikes between production and demand becomes much more powerful in a 2050


energy system and storage systems will play a vital role in the H2O system in order to help balance supply and demand, by serving as a buffer for the CHP plant.

The CO2 system has a lower degree of utilization of heat from the CHP plant, as there is simply too little heat demand in the system, especially during the summer where most of the excess heat from CHP plants is just cooled away. The CO2 system is also producing additional CO2 vapor from the cooling systems, and with no consumers able to utilize the vapor, it has to be condensed by the sea based liquid production. This further increases the electricity consumption to power pumps, and if the wind is not blowing, the CHP plant has to cover the demand and as a result waste more heat in the process.

The last graph shows the remaining demand after balancing measures where the CO2 system generally seems to have a higher demand throughout the year, but this graph includes consumption for balancing the cooling systems in the CO2 system and not the power consumption for the cooling systems in the H2O system. The reason for this is that the H2O system consumes electricity for cooling purposes and just releases excess no-useful heat to the surroundings, which does not require any balancing measures. Primary fuel used to produce electricity for the H2O cooling systems are however included in Figure 56, where an overview of the total biomass consumption is illustrated.

Figure 55: Thermal production need in each system to balance electricity and heat demand


Figure 56: Overall biomass consumption in CO2 system and H2O storage system

The final result of biomass consumption shows a very fluctuating demand throughout the year, which is obviously following the large fluctuations from heat and power productions.

An overview of the yearly biomass consumption can be seen in Table 41, where the CO2 system performs 3% worse than the H2O system over an entire year, which is an improvement of the CO2 system by 5% compared to the base scenario.

Yearly total biomass consumption

[ton] [%] H2O 15993 Base CO2 16469 3.0%

Table 41: Yearly biomass consumption in each system

The CO2 system uses a bit more biomass than the H2O system, it was expected that the CO2 system would perform significantly better, when introducing high shares of fluctuating energy sources. One of the main reasons why this is not the case, is that 80% of the boilers are replaced by large heat pumps and has given the H2O system the opportunity to produce heat more efficiently in hours where power production from fluctuation sources is high. In these hours the CHP plant would overproduce electricity in order to meet the heat demand, thus boilers would have been operated instead, but with large heat pumps heat can be produced more efficiently from the available electricity instead of using primary fuel to run boilers directly. Implementing large heat pumps saves the H2O system around 2000 tons extra biomass each year and without them the CO2 system would have used 8.4% less than the H2O system.

It is worth noticing that a reduction of 44% and 41% primary fuel is obtained in the CO2 system and H2O system respectively when compared to the base scenario from the model inputs made. Even though this is a significant reduction, there is still plenty of room for optimization when considering especially the low degree of utilization of the heat production from the CHP plants.


17 Overview of system performances and comparisons Table 42 sums up all the scenarios and sensitivity analysis carried out. The red and green background in the primary fuel columns indicates which system is preferable in each investigation. In the comparison column, a green color indicates an improvement in the system performance, compared to the base scenario with regard to the CO2 system. The red color indicate the opposite, while the black color means unchanged performances.

Case CO2 based system

H2O based system

Comments

Primary fuel Primary fuel Comparison [ton] [ton] [%] Base scenario 29292 27131 8.0 Storage hot water 29292 27131 8.0 10 hours, only in CO2 system Storage liquid/vapor 29272 27131 8.0 10 hours, only in CO2 system Less office, increased supermarket 27842 27430 1.5

Less office, increased residential and supermarket

29218 28708 1.8

Less mall and supermarket, more residential

29986 27241 10.1

Ørestaden 26046 25103 3.8 Only mall 23846 24455 2.5 Only residential 32680 29919 9.2 Only supermarket 12912 27837 -53.6 Only office 26366 24455 7.8 Variations in ground temperature; 3°C 29568 27131 9.0 3°C ground temperature

Variations in ground temperature; 13°C 28814 27131 6.2 13°C ground temperature

Solar power 20805 21142 1.6 Extreme case: 50% Solar power

Solar heating 29292 25921 13.0 Extreme case: 50% Solar heating

Geothermal 29292 24698 18.6 Extreme case: 50% Geothermal

Electricity produced from non-thermal sources – Base scenario

29435 36572 -19.5 100% Electricity imported

Electricity produced from non-thermal sources – Heat pump scenario

29435 33948 -13.3 100% Electricity imported, 100% heat pumps

2050 Scenario 16494 15993 3.0 Table 42: Summarized results from all the simulated scenarios and sensitivity analysis.


18 Economical considerations Investment and maintenance costs in the CO2 based energy system are very difficult to predict, or even give a qualified estimate of, as the system is very comprehensive and with a lot of unknown variable parameters. The fact that no such system exists means that no previous data can be used to ease the prediction. In this assessment a simple comparison of investment and maintenance costs between the CO2 based system and the H2O based system has been made. The economic comparison seen in Table 43 considers chosen areas within the systems and expected impacts on investment costs are briefly explained.

CO2 based system H2O based system Planning,

projection and execution

Comprehensive planning, projection and execution as the system is new. Much know-how and experience in Denmark.

Pipelines

Higher requirements to material selection, due to high pressure and corrosion. Smaller

pipe diameters and less insulation are needed. Digging down the pipes are the

same as the H2O based system.

Fewer requirements to pipes, but higher demand for insulation, and larger pipe

diameters.

Network fluid Pure CO2 is more expensive than water H2O is cheaper than pure CO2 Sea water

cooling Sea water cooling needed as cold source to

balance system and at the power plants. Except power plant cooling, no additional

cooling is needed in the network.

Safety and control

Many sensors, ventilation systems, block valves, water content control, and other

safety and control components are needed.

Much less need for safety and control equipment in the network.

Maintenance Due to the increased amount and

complexity of equipment, maintenance cost will be higher in the CO2 system.

The maintenance costs are very low since the main part of the system is pipes and simple

heat exchangers.

Supermarkets

Same refrigeration system but CO2 branch pipes has to be installed to connect to

pipelines. Comfort cooling only need a heat exchanger, but extra heat pump has to be

installed.

Same refrigeration system, but comfort cooling system is needed. However only a

heat exchanger is needed to gain heat from district heating.

Malls Heat pumps have to be installed but only

need for a heat exchanger to provide comfort cooling.

Only a heat exchanger to provide heating but comfort cooling system is needed.

Office buildings

Heat pumps have to be installed but only need for a heat exchanger to provide

comfort cooling.

Only a heat exchanger to provide heating but comfort cooling system is needed.

Residential buildings Heat pumps have to be installed. Only a heat exchanger to provide heating.

Overall comparison

The CO2 based system will be more expensive to invest in, mainly because

much more equipment is needed decentrally to utilize the CO2 and because

more components are needed due to safety aspects.

The H2O based system will be the cheapest solution in regards to the investment cost.

Additionally much experience and know-how in Denmark which simplifies matters. The use

of water drastically reduced the need for decentral equipment as well as safety and

control components. Table 43: Comparison of investment costs


18.1 Current tax legislations on utilization of waste heat. If implementation of the CO2 based system should occur, then all consumers would to some degree become producers of another energy service, with the current tax legislation in Denmark this could potentially pose a problem, which is why a quick explanation of the system will be given.

Current energy tax legislation regarding utilization of waste heat aims at creating a balance between benefits from the producer point of view and from a socio-economical point of view. The complex energy tax legislations, however do not create many incentives to invest in equipment utilizing the waste heat because the tax rates are high.

In regards to utilization of waste energy from an industrial production the current tax legislations distinguish clearly between when waste energy, mainly heat, from a production is taxable and when it is not. Waste energy from one production process utilized in another process internally in the production facility is considered tax free, as tax has already been paid on the energy source utilized for the process whether it is a fuel or electricity. If waste energy is available and leaves the site of production to become available for external utilization it is considered taxable. The reason for this distinction is to avoid incentives for producers of excess energy to increase production intentionally, in order to benefit from the earnings from selling the tax free energy at low rates. The waste energy, heat for example, could be sold to district heating plants, where both parties would benefit from the trade, this is however against international competition law, which is the reason for the taxation.

The same taxation laws could be a major barrier for the CO2 system, as the system is centered around the pretense that the consumers are “producing” energy for other consumers to utilize. More specifically, input electricity is used to produce the thermal energy service at the consumer site using heat pumps, and heat energy is either removed or added to the site of production thereby becoming available in the pipeline. This would then be subject to a taxation of the amount of energy delivered. Incentives to be connected to a CO2 system would thereby be non-existing, as a consumer is then subjected to a taxation because the energy are made available to other consumers instead of just releasing it to the ambient.

Therefore, the CO2 system cannot feasibly be operated with the present energy tax legislations, and if the CO2 system is to be implemented in the future, then it would require a change of these taxation laws, as the consumers would not benefit economically from delivering energy to the network.


19 Conclusion A novel district energy system based on CO2 has been proposed as an alternative to the present H2O based thermal energy system, in an attempt to mitigate its current and future drawbacks. In order to evaluate the performance of the novel system, a case has been constructed and used as a platform for comparison between the two systems. The case is constructed based on data about consumption of energy services, production sources available and building distribution in Copenhagen city center.

Calculations of system performances have been made in a constructed Excel simulation model which includes hourly consumption data for the chosen consumer types and production units with the necessary assumptions for simplification. This model additionally enables the possibility of introducing a variety of changes to the energy system, with regard to production, consumption and building distribution. The changes implemented are utilized both in connection with a direct system comparison, where a range of changes are implemented simultaneously, and later in a series of sensitivity analysis, where the impact of specific changes to the systems are determined.

The results obtained from the simulation model showed, that based on the current situation in Copenhagen the present H2O system is preferable as it performs 8% better than the proposed CO2 system. One of the main reasons for this result is, that most of the power production for Eastern Denmark is produced by CHP plants in Copenhagen, which makes excess heat easily available for district heating purposes, thereby benefitting the H2O system. With a COP of nearly 10 for heat production at the Avedøre CHP plant block 1, the H2O system is much more efficient at meeting the heat demand of the consumers compared to the CO2 system, which must produce the heat from electrical driven decentral heat pumps with a significantly lower COP. This aspect is further strengthened by the fact that heating demand is much higher than cooling demand in the base scenario, mainly because of the large share of residential buildings, which only demand heating.

A series of sensitivity analysis have been carried out to determine the impact on primary fuel consumption when introducing a variety of changes to the systems.

It was shown that introducing storage to the CO2 system, both as hot water storage and as liquid/vapor buffer, does not have a significant impact on the system performance. The reason being that the CO2 system already has great system balancing capabilities and there is no particular need for additional balancing measures. This matter is additionally highlighted when introducing solar and geothermal heating to the systems, where the CO2 system again shows limited influence because the additional heat is not needed.

When varying the building distribution results show a large impact on consumption of primary fuels. The general trend is that the more cooling demand introduced to the system the better the CO2 system performs compared to the H2O system. This is particularly clear in the extreme case with only supermarket consumption included, which shows the CO2 system only using 53.6% of the primary fuel used in the H2O system.

When limiting the possibility of excess heat from CHP production to the systems, the results clearly indicate that the CO2 system is by far the most efficient system. In situations where 35 % or more of the electricity is


produced without combined heat production, the CO2 system has the smallest primary energy consumption. If no excess heat is available from electricity production not even the implementation of heat pumps in the H2O system can close the gap, unless COP values in excess of 4.8 is assumed.

A 2050 scenario has been made, based on predictions found in literature, where changes to the composition of production sources of electricity and heat, as well as energy savings are implemented in the simulation model. Results shows that the primary fuel consumption obviously decrease significantly in both systems, but the H2O system still proves to be the most efficient system and performs 3% better.

The comparative assessment carried out in this thesis have shown that under the right circumstances, especially with regard to the heating and cooling demand ratio and the availability of a CHP plant, the proposed CO2 based district energy system is highly advantageous compared to the present H2O based system. Under the present circumstances however, the availability of reject heat from CHP production ensures that the H2O system is the better choice.

In addition, the qualitative assessment of financial aspects of the system indicates that the investment and maintenance costs will be far greater with the CO2 system than the present one.


20 Future work Based on the assessment carried out and the limitations needed to be made, several different aspects have not been included in the project, which could be interesting to consider in future investigations and projects.

20.1 Different CO2 system layouts The proposed CO2 system is centered on the pretence that CO2 is provided to the consumers through transmission- and distribution lines and branch pipes. This is not a definite solution and it could be interesting in future projects to investigate different system lay-outs, for instance a hybrid system which have CO2 in a transmission network able to utilize low temperature energy sources and additionally have low heat losses to the surrounding soil. CO2 is able deliver energy through phase change to H2O based distribution networks that provide district heating and district cooling to consumers.

20.2 Practical test system A CO2 based district energy system does not presently, therefore it would be of great interest to make a pilot project where a small scale system could be operated and tested. Such a test system can provide important information regarding the thermodynamic behavior of the system. Information obtained from operating the system can serve as an identification of unforeseen problematic issues, a verification of the theoretical predictions and basis for optimization projects.

20.3 Optimization of heat pump cycles in CO2 system This assessment has its main focus on the comparative aspect between the two district energy systems and an elaborate optimization of the CO2 cycles has not been made. In future projects, it could be interesting to look into optimizing each cycle in order to reach higher COP values, which could improve the overall system performance of the CO2 system. In that regard an exergy analysis would be obvious to carry out on the cycles in order to identify where the largest exergy destructions are, thus where the largest improvement can be obtained by optimization.

20.4 Comprehensive risk assessment Safety aspects will play a key role in the public acceptance of the system, as CO2 could potentially be lethal in worst case. A short risk assessment has been made in this assessment to highlight than most obvious risks associated with having a CO2 based system, but it is strongly recommended to make a comprehensive risk assessment which deals with every possible risk related aspect. No CO2 system presently exists, but it could be imagined that experience with natural gas systems and perhaps information from operating a possible CO2 system pilot project could be used in a future risk assessment.

20.5 Economical investigation of CO2 system The economical aspect has only been briefly dealt with in this preliminary assessment due to uncertainty issues. At the present stage of development the economics related to the CO2 based system is very difficult to give qualified estimation of, primarily with regard to investment costs and maintenance costs as no similar reference system exists. In potential future projects an economic assessment would be a very


important investigation, because the economics are obviously the prime mover when choosing the energy system to for instance supply a green field area. Such an assessment could perhaps also be a important factor when considering whether or not to develop the CO2 system any further.


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[53] Energistyrelsen C. (2011, July) http://www.ens.dk/da-DK/Info/TalOgKort/Statistik_og_noegletal/Energipriser_og_afgifter/Kulpriser/Sider/Forside.aspx.

[54] Wikipedia. (2010, May) http://da.wikipedia.org/wiki/%C3%98restad.

[55] Energistyrelsen B, "Energistatestik 2009," København, ISSN www: 0906-4699, 2009.

[56] R. Schindler, "Towards green energy: Challenges and options.," Fraunhofer Institute for Solar Energy Systems, ISE, Freiburg, Presentation.

[57] Rambøll homepage. (2011) http://www.ramboll.dk/projects/viewproject?projectid=E6DE18D4-3D33-493C-87E9-C9A37E601554.

[58] Energinet.dk B, "Energi 2050 - Udviklingsspor for energisystemet," Fredericia, Doc.no. 41538/10, Case 10/3378, 2010.

[59] Dansk Energi, "Power to the people," 2009.

[60] Klimakommissionen (B), "Dokumentationsdelen til klimakommissionens samlet rapport - Grøn Energi," 2010.

[61] Pumps and systems. http://www.pump-zone.com/compressors/compressors/why-compression-ratio-matters.html.

[62] B. Elmegaard and N. Houbak, "Simulation of the Avedøreværket unit 1," in Simulator contest proposed for the ECOS 2003 conference, 2003.

[63] Christian Berg Køling A/S. (2007) http://www.christianbergkoling.dk/forside/nyanlaeg/koelemiddel/hfcerne/.

[64] F-Chart Software, "EES - Engineering Equation Solver," 2010.

[65] Brian Elmegaard, "Simulation of boiler dynamics - Development, Evaluation and Application of a General Energy System Simulation Tool," 1999.

[66] Wikipedia. (2011, April) http://en.wikipedia.org/wiki/Carnot_cycle.

[67] AIA Calc. (2011) http://www.tt-coil.dk/Default.aspx?PagId=96.

[68] Bitzer Software. (2011) http://bitzer.de/eng/productservice/software/1.

[69] Jan Lassen TT Coil A/S, Personal Correspondance, 2011, Regarding use of common refrigerant in


comfort cooling cycles.

[70] DTU-MEK. http://www.et.web.mek.dtu.dk/coolpack/download.html.

[71] Heat Exchange Institute, "Tech Sheet #113," 2005.

[72] SBi, "Varmt brugsvand - Måling af forbrug og varmetab i cirkulationsledninger," 2009.

[73] C.S. Poulsen, "Varmepumper – vær sikker på, at du køber et kvalitetsprodukt, der passer til netop dit hus," Teknologisk Institut, 2006.

[74] Danish Ministry of the Environment, "Statutory Order no. 552 of 2 July 2002 - Regulating Certain Industrial Greenhouse Gases," 2002.

[75] Bitzer, "KT-660 - 2, Application of Propane (R290) with semi-hermetic Reciprocating Compressors," 1997.

DTU Mechanical Engineering

Section of Thermal Energy Systems

Technical University of Denmark

Nils Koppels Allé, Bld. 403

DK- 2800 Kgs. Lyngby

Denmark

Phone (+45) 45 25 41 31

Fax (+45) 45 88 43 25

www.mek.dtu.dk

Appendix

Effi ciency Assessment of a Conventional District Energy System and an Alternative CO2 Based Solution

Mas

ter

Thes

is

Christian Vang MadsenChristian Nørr JacobsenMEK-TES-EP-2011-14August 2011

Appendix – Efficiency Assessment of a Conventional District Energy System and an Alternative CO2 Based Solution Page 1/88

Table of Contents

Table of Contents .............................................................................................................................................. 1 Appendix 1 – Simulation programs ................................................................................................................... 2 Appendix 2 – Definition of Coefficient Of Performance (COP) ......................................................................... 4 Appendix 3 – Comfort Cooling in the H2O system ............................................................................................. 6 Appendix 4 – Dry cooler, H2O based comfort cooling ..................................................................................... 13 Appendix 5 – AIA Calc simulation output - dry cooler in comfort cooling cycle. ........................................... 15 Appendix 6 – Refrigeration H2O system .......................................................................................................... 16 Appendix 7 – Air cooled condenser, Refrigeration cycle in the H2O based system ........................................ 22 Appendix 8 – Log ph diagrams ........................................................................................................................ 23 Appendix 9 – CHP Vapor production CO2 based system ................................................................................. 27 Appendix 10 – Comfort Cooling CO2 based system ......................................................................................... 30 Appendix 11 – Refrigeration in CO2 based system .......................................................................................... 33 Appendix 12 – CO2 heat exchanger from Alfa Laval ........................................................................................ 40 Appendix 13 – Open Loop Domestic Hot Water – OLDHW ............................................................................. 42 Appendix 14 – CO2 gas cooler from Alfa Laval ................................................................................................ 51 Appendix 15 – Closed Loop Domestic Hot Water – CLDHW ........................................................................... 52 Appendix 16 – Choice of refrigerant in closed loop cycle ............................................................................... 60 Appendix 17 – Case description and hourly data derivation malls ................................................................. 62 Appendix 18 – Case description and hourly data derivation of supermarkets ............................................... 63 Appendix 19 – Obtained data from Føtex in Frederikssund ........................................................................... 66 Appendix 20 – Case description and hourly data derivation of office buildings ............................................. 72 Appendix 21 – Case description of residential sector ..................................................................................... 74 Appendix 22 – Excel Workbook ....................................................................................................................... 77 Appendix References ....................................................................................................................................... 87

Contents of Compact Disc (CD)

The enclosed CD can be found on the last page of this appendix and contains the following items:

• Excel files • DNA files • EES files • Utilized references • Digital representation of the report and appendix.


Appendix 1 – Simulation programs

Engineering Equation Solver (EES)

The EES manual [1] has been used to write this short description of the program.

The basic function in EES is to solve algebraic equations, but differential equations and equations with complex variables can be solved as well. EES is also capable of doing optimizing by iteration, linear- and non-linear regressions and making plot and animations. User interface and commands are simple and intuitive, but the program is also advanced enough for expect users, making the EES suitable to broad range of skill levels.

What separates EES from most other numerical simulation software tools is that the program solves a group of equations simultaneously, meaning the equations do not have to be written in a correct order to be able to execute the programming code. This enables solving equations iteratively and design problems where two parameters are internally dependent of each other. EES provides this ability with a parametric table where variations of one parameter can be stated and a dependent unknown parameter can be calculated from each input. EES also has an extensive built-in library of mathematical and thermodynamic property functions, which can be called from two other properties. This feature is very helpful when solving thermodynamic equations as properties of refrigerants and brines at different states can be easily included in equations. EES is compatible with high level programs such as Pascal, C and FORTRAN, as well as being able to print to PDF and LaTeX format.

Dynamic Network Analysis (DNA)

The DNA manual [2] has been used to write the short description of the simulation program.

DNA is an energy simulation tool, based the Emacs platform, able to make simulations on both steady state and dynamic models, as well as being able to solve numerical algebraic and differential equation systems. The program has a built-in components list and thermodynamic state models for fluids, which can be called in the input file. This dramatically limits the extent of the programming code needed to model an energy system.

The energy system must be modeled component wise in the input file in relation to figure 1, where each component is called and connected to components before and after by nodes.


Steady state parameters, conditions and start guesses of unknown values can be stated in the input syntax. The output file contains all thermodynamic states in each note, which can be used to get an overview of the energy system, and make optimization easier. For optimization purposes the program has a build-in exergy function, which from a reference pressure and temperature is able to give the exergy flow in each note, meaning the notes with high exergy destruction can be identified.


Appendix 2 – Definition of Coefficient Of Performance (COP)

The following references have been used to write appendix 2; [3][4][5][6].

The general COP of a refrigeration cycle is defined by the ratio between the heat transferred to the cycle and the electrical input and is given by following equation:

𝐶𝑂𝑃� = ��

(1)

Where 𝑄� is the heat transferred to the cycle 𝑊 is the work input to the cycle

An additional general COP can be defined for a heat pump cycle, where it can be defined as the ratio between heat rejected from the cycle and the electrical input. The COP is given by following equation:

𝐶𝑂𝑃� = ��

(2)

Where 𝑄� is the heat rejected from the cycle 𝑊 is the work input to the cycle A heat pump is able to produce both heating and cooling and the COP is different in these cases. The COP of cooling is defined as in (1) and heating is as defined in (2). If all heat rejected from the cycle is useful 𝑄� = 𝑄� + 𝑊 is valid. Combining this with (1) and (2) it can be seen that the relation between 𝐶𝑂𝑃� and 𝐶𝑂𝑃� is:

𝐶𝑂𝑃� = 𝐶𝑂𝑃� − 1 (3)

According to the first law of thermodynamics it is shown that 𝑄� = 𝑄� + 𝑊 𝑊 = 𝑄� − 𝑄�. By substituting 𝑊 with 𝑄� − 𝑄� in equations (1) and (2) it gives:

𝐶𝑂𝑃� = ��

(4)

𝐶𝑂𝑃� = ��

(5)

The Carnot cycle gives the maximum theoretical efficiency of any refrigeration cycle or heat pump cycle. The optimal Carnot cycle is achieved by having no irreversibilities in the cycle, but it is not possible as all systems have irreversibilities in the throttling process and in the compression process.

From Carnot the maximum theoretical heat transfer can be expressed as the integral of temperature in relation to the change in entropy.

𝑄� = ∫𝑇 ∗ 𝑑𝑠 (6)

Where


𝑄� is the heat transfer to a reversible process

Solving the integral gives a solution of both a heat pump cycle and a refrigeration cycle.

𝑄� = 𝑇� ∗ ∆𝑠 (7)

𝑄� = 𝑇� ∗ ∆𝑠 (8)

Where 𝑄�is the heat transfer from the cycle 𝑄� is the heat transfer to the cycle 𝑇� is the absolute condensing temperature 𝑇� is the absolute evaporating temperature ∆𝑠 is the difference in entropy

The work done by the Carnot cycle is expressed by the absolute temperature difference times the entropy difference.

𝑊 = (𝑇� − 𝑇�) ∗ ∆𝑠 (9)

Substituting 𝑄�, 𝑄� and 𝑊 in equation (4) and (5) gives:

𝐶𝑂𝑃� = ��

(10)

𝐶𝑂𝑃� = ��

(11)

The maximum theoretical efficiency following the Carnot cycle is entirely dependent on the evaporation and condensing temperatures following equation (10) and (11). Lower temperature differences between 𝑇� and 𝑇� gives the higher the COP. Below a table and a plot has been made to show the maximum theoretical COP follow the Carnot cycle. The evaporation temperature has been set to 8°C as the CO2 temperature in the district energy network, and the condensing temperature is the variable.

0.00

10.00

20.00

30.00

40.00

50.00

15 25 35 45 55 65 75 85 95

COP

Condensing temp [*C]

Maximum theoretical COP

COP_H COP_C


Appendix 3 – Comfort Cooling in the H2O system

Comfort Cooling – CC

Comfort cooling is becoming increasingly widespread in Denmark, mainly in office buildings, malls, supermarkets and other public places. Some residential houses also have comfort cooling installed, but this is not common, thus this will not be including in the initial systems. Comfort cooling can be provided either by central production through a district cooling network or produced decentral by individual systems. Though Copenhagen has a district cooling central near Kgs. Nytorv supplying large consumers at the city center [7], it is chosen to assume that comfort cooling will be provided by decentral production as this is the most common practice in the present energy system.

System diagram

A system diagram of the comfort cooling cycle can be seen in Figure 1 below.

Figure 1: System diagram of the comfort cooling cycle in the water based energy system

Refrigerant

A natural refrigerant is desired due to the low global warming potential (GWP) and ozone depletion potential (ODP). However, according to Jan Lassen, TT Coil A/S, the common practice is to use the HFC refrigerant R410A in comfort cooling systems [8]. HFC refrigerant are restricted though due to European Union (EU) laws, [9] but large scale comfort cooling plants are no problem as long as the units are separated, because the restrictions only applies to one unit and not the entire plant. The modeling of the existing system aim to replicate the real conditions and R410A is chosen as the refrigerant based on information provided.

Evaporator

The evaporator used in the comfort cooling cycle is assumed to be the same type, as the one obtained from Alfa Laval, see Appendix 12. In Table 1 an overview of the evaporator parameters are shown.


Evaporator parameters Unit Refrigerant R410A Tw in 18 °C Tw out 10 °C Tevap 0.5 °C Tsup 7 K �̇�R410A 0.5 kg/s �̇�H20 2.39 kg/s

Table 1: Evaporator parameters in the comfort cooling cycle

It has been chosen to have an evaporation temperature of 0.5°C to avoid any problems with the water being cooled in regards to any potential freezing. The amount of superheat has been chosen based on personal correspondence with Jan Lassen TT Coil A/S [8].

Dry cooler and condenser

An air cooled condenser were originally chosen as condenser type, but calculations made by TT Coil A/s showed a surface area and pressure loss on the refrigerant side way to high.

Focus was then shifted to a dry cooler which requires an intermediate loop between dry cooler and condenser. Brine is circulated in this loop and is air cooled by fans in the dry cooler and serves as a heat sink in the condenser.

The condenser chosen will be the same type as the evaporator in this cycle due to the same reasons. In the condenser a constant subcooling of 5K will happen regardless of condensing temperature.

In order to find a dry cooler, a pressure drop at the brine side and fan power consumption to be used in the simulations, an air-cooled condenser simulation tool, AIACalc, have been used [10]. The tool is specifically developed for air cooled condensers using Hydro Fluor Carbon (HFC) refrigerants.

The dry cooler was found from a variety of parameter inputs whereas the most important ones are capacity, air inlet temperature, and fluid data of the brine in the intermediate loop. Inputs are standard dimensioning numbers provided by Jan Lassen, TT Coil A/S. See Appendix 4.

Relevant inputs to AIA Calc are stated in Table 2 below:


AIA Calc parameter inputs Unit Type X2-C 2.1 Refrigerant R410A �̇�Cond 120 kW

TCond 45 °C Tair in 30 °C

Table 2: AIA Calc parameter inputs

Results from the simulation were a list of possible suited dry coolers, but it was chosen to have a dry cooler with an air flow a bit higher than to the required air flow calculated in DNA. Simulation outputs from AIA Calc can be seen in


Appendix 5, but the most important results are stated in Table 3 below:

Dry cooler main results Unit Brine Ethylene Glycol 30% Δpbrine 61000 Pa Wfan 4.51 kW

Table 3: Main results of dry cooler unit

Compressor

From Bitzer software a scroll-compressor has been chosen, which is a typical choice in regards to R410A in comfort cooling applications.

In order to calculate the isentropic efficiency, to be used in the simulation program DNA, from the desired evaporation- and condensation temperatures and other compressor settings, software from Bitzer was used [11].The software provides 10 unique coefficients for capacity (X) and compressor work (Y) for the chosen compressor type. The coefficients are to be used in the following general equation given in the Bitzer software:

𝑿 = 𝑪𝟏 + 𝑪𝟐 ∗ 𝑻𝒆𝒗𝒂𝒑 + 𝑪𝟑 ∗ 𝑻𝒄𝒐𝒏𝒅 + 𝑪𝟒 ∗ 𝑻𝒆𝒗𝒂𝒑𝟐 + 𝑪𝟓 ∗ 𝑻𝒆𝒗𝒂𝒑 ∗ 𝑻𝒄𝒐𝒏𝒅 + 𝑪𝟔 ∗ 𝑻𝒄𝒐𝒏𝒅𝟐 + 𝑪𝟕 ∗ 𝑻𝒆𝒗𝒂𝒑𝟑 + 𝑪𝟖 ∗ 𝑻𝒄𝒐𝒏𝒅 ∗ 𝑻𝒆𝒗𝒂𝒑𝟐

+ 𝑪𝟗 ∗ 𝑻𝒆𝒗𝒂𝒑 ∗ 𝑻𝒄𝒐𝒏𝒅𝟐 + 𝑪𝟏𝟎 ∗ 𝑻𝒄𝒐𝒏𝒅𝟑

𝒀 = 𝑪𝟏 + 𝑪𝟐 ∗ 𝑻𝒆𝒗𝒂𝒑 + 𝑪𝟑 ∗ 𝑻𝒄𝒐𝒏𝒅 + 𝑪𝟒 ∗ 𝑻𝒆𝒗𝒂𝒑𝟐 + 𝑪𝟓 ∗ 𝑻𝒆𝒗𝒂𝒑 ∗ 𝑻𝒄𝒐𝒏𝒅 + 𝑪𝟔 ∗ 𝑻𝒄𝒐𝒏𝒅𝟐 + 𝑪𝟕 ∗ 𝑻𝒆𝒗𝒂𝒑𝟑 + 𝑪𝟖 ∗ 𝑻𝒄𝒐𝒏𝒅 ∗ 𝑻𝒆𝒗𝒂𝒑𝟐

+ 𝑪𝟗 ∗ 𝑻𝒆𝒗𝒂𝒑 ∗ 𝑻𝒄𝒐𝒏𝒅𝟐 + 𝑪𝟏𝟎 ∗ 𝑻𝒄𝒐𝒏𝒅𝟑

The equations serve as input to Engineering Equation Software, (EES), see EES file ”compressor selection”, from which the isentropic efficiency is calculated. In Table 4 compressor information are shown, and in Table 5 the isentropic efficiency as a function of varying condensing temperature are shown. The condensing temperatures will vary during the year due to changing outdoor temperatures.

Compressor selection Producent Bitzer Type GSD80421VA Refrigerant R410A

Table 4: Compressor information, comfort cooling

TCond ηis

[°C] [-] 10 0.4096

12.5 0.4705 17.5 0.5645 22.5 0.6297 27.5 0.6715 32.5 0.6933 37.5 0.6976 42.5 0.6865 45 0.6758


Table 5: Isentropic efficiency of the compressor as a function of condensing temperature

Results

To make the calculations of COP of the cycle several assumptions has been made. The temperature lift of the ambient air will be 7.5K regardless of ambient temperature, even though it in practice will be very hard to control this exactly. Additionally, power consumptions of the fans in the dry cooler are also assumed constant. Calculations have been made down to outdoor temperatures of -20°C, as consumption data obtained from malls and office buildings shows a demand for comfort cooling even during the winter. The results of the comfort cooling cycle can be seen below in Table 6:

Comfort cooling final results Tamb step Tcond �̇� Wfan Wtot COP �̇�R410A �̇�air

[C] [°C] [kJ/s] [kW] [kW] [-] [kg/s] [kg/s] -20 10 80 4.51 12.21 6.55 0.36 11.58

-17.5 10 80 4.51 12.21 6.55 0.36 11.58 -12.5 10 80 4.51 12.21 6.55 0.36 11.58 -7.5 10 80 4.51 12.21 6.55 0.36 11.58 -2.5 12.5 80 4.51 12.95 6.18 0.37 11.68 2.5 17.5 80 4.51 14.55 5.50 0.38 11.89 7.5 22.5 80 4.51 16.38 4.88 0.4 12.13

12.5 27.5 80 4.51 18.52 4.32 0.41 12.41 17.5 32.5 80 4.51 21.09 3.79 0.43 12.75 22.5 37.5 80 4.51 24.26 3.30 0.46 13.17 27.5 42.5 80 4.51 28.26 2.83 0.48 13.69 30 45 80 4.51 30.68 2.61 0.5 14.01

Table 6: Results of the comfort cooling cycle in the water based district energy system

Cycle illustration

In Figure 2 the comfort cooling cycle in a log ph diagram of R410A is shown with different condensing temperatures.


Figure 2: Cycle illustration of comfort cooling cycle in the water based system, with different condensing temperatures.

DNA code - comfort cooling cycle

TITLE DNA model of the comfort cooling cycle in the H2O based system C WBCC = Water based condenser c Defining the compressor and cycle media struc WBCC_Compressor compre_1 404 401 300 100 .6758 1 media 404 R410A addco tsat 401 10 start q WBCC_Compressor 300 0 start W WBCC_Compressor 100 15 start m WBCC_Compressor 404 1 C Defining the condenser struc WBCC_Cond heatex_1 401 402 601 602 301 0.0611 0 media 601 SIMPLE_AIR addco T WBCC_Cond 601 -20 addco T WBCC_Cond 602 -12.5 addco p 601 1.01325 start m WBCC_Cond 601 1 addco T WBCC_Cond 402 7 addco q WBCC_Cond 301 0


c Defining the throttling valve struc WBCC_Valve valve_01 402 403 addco tsat 403 5 c Defining the evaporator struc WBCC_heatex heatex_1 701 702 403 404 302 0.113 0.0611 media 701 STEAM start m WBCC_heatex 701 0.5 addco p 701 6 addco T WBCC_heatex 701 18 addco T WBCC_heatex 702 10 addco T WBCC_heatex 404 7 addco q WBCC_heatex 302 0 c Defining the 'heat source' at the consumers struc WBCC_HS heatsrc0 702 703 901 0.113 addco q WBCC_HS 901 80 c Defining the loop pump struc WBCC_pump2 liqpum_1 703 701 201 0.95 start e WBCC_pump2 201 5


Appendix 4 – Dry cooler, H2O based comfort cooling

E-mail from Jan Lassen, TT Coil where he makes it clear that a normal air cooled condenser cannot be used with the inputs from the comfort cooling cycle, and a dry cooler is suggested instead.

Jan Lassen <[email protected]> Fri, Jul 15, 2011 at 12:34 PM To: Christian Nørr Jacobsen <[email protected]>

Eks

Dette er for vedhæftede eksempel

Som du kan se af dm3 er indholdet for stort

Derfor vælges en tørkøler løsning

Regnes efter 120 kw ude 30 grader 30% etg samt mediun ind / ud på 40 / 35 grader

Hilsen

tt-coil a/s JanLassen ExportEngineer [email protected] Tempovej18-22 DK2750Ballerup tel: +4544200400

fax: +4544200410 mobile: +4523246643 www.tt-coil.dk Skype ID:lassen

mailto:[email protected]

http://www.plaxo.com/click_to_call?lang=en&src=jj_signature&To=%2B45+44200400&[email protected]

http://www.plaxo.com/click_to_call?lang=en&src=jj_signature&To=%2B45+23246643&[email protected]

http://www.tt-coil.dk/



Appendix 5 – AIA Calc simulation output - dry cooler in comfort cooling cycle.

The screen shot is from the simulation program AIA Calc and shows information regarding the dry cooler used in the comfort cooling cycle in the H2O based system.


Appendix 6 – Refrigeration H2O system

Purpose

In the current system, the standard means of obtaining refrigeration is using a normal compression cycle with an outside air condenser. In the constructed scenario, the only area utilizing low temperature refrigeration are supermarkets, therefore the refrigeration system simulated will be constructed based on the demands of these systems.

System diagram

Because the needed temperatures are very low, -15°C for cooling and -35°C for freezing [12][13], a brine is avoided and instead the refrigerant is sent directly to the refrigerated areas, leading to a situation where the pressurized refrigerant is transported throughout areas where the customers are shopping. This raises demands that the refrigerant must be both nontoxic and inflammable, which, combined with restrictions on HFCs, leads to R744 (CO2) being the current industry standard in supermarket refrigeration systems.

There are many possible ways to construct a supermarket refrigeration system, but to ensure a fair comparison the same system construction is assumed to be used in both the CO2 and H2O system, with the obvious exception that the two supply lines connected to the outside air condenser/gas cooler, dependent on ambient temperatures, in the H2O system, is instead connected to the proposed CO2 network.

Figure 3: H2O refrigeration system diagram, numbers correspond to nodes in the DNA code

Condenser

The outside condenser is responsible for condensing the refrigerant by removing energy from the refrigerant stream.

To do this the refrigerant stream must have a condensing temperature above that of outside air, which varies throughout the year. To take this into account, a Danish weather reference year is utilized to adjust the refrigeration systems COP according to the outside temperature. As a simplification, the temperature range from -20°C to 30°C is split into steps of 5°C, meaning that 12 simulations are conducted each of which returns a COP value which can then be used to calculate the needed amount of electricity from the refrigeration cycle at the different hours throughout the year.


In each simulation the condensation temperature is adjusted to optimize the COP of the system, while the output air is assumed heated 15K and the refrigerant assumed cooled to 2K above ambient air temperature, thereby making the airflow variable. The refrigerant side pressure drop across the condenser is assumed to be similar to that of the evaporators. Based on consumption values obtained from AIA Calc,[10] the fans used to transport the air through the condenser is assumed to consume a constant 1.56kW. For data sheet see Appendix 7.

Results

Based on the mentioned considerations, the refrigeration system has been modeled in DNA, resulting in the following values for a range of outside temperatures.

Tout step Condensing or Transcritical �̇�air Pcomp Wtot COP

[C] [kg/s] [bar] [kW] -20 Condensing 5.86 30.65 10.28 7.78

-17.5 Condensing 5.96 32.79 11.81 6.77 -12.5 Condensing 6.08 35.03 13.64 5.87 -7.5 Condensing 6.31 39.87 17.09 4.68 -2.5 Condensing 6.55 45.19 20.87 3.83 2.5 Condensing 6.83 51.02 25.04 3.19 7.5 Condensing 7.03 54.15 28.09 2.85

12.5 Condensing 7.37 60.85 33.33 2.40 17.5 Transcritical 7.96 75.177 42.3 1.89 22.5 Transcritical 8.22 75.177 46.18 1.73 27.5 Transcritical 8.7 75.177 53.54 1.49 30 Transcritical 9.09 85.177 59.41 1.35

Table 7: COP calculation for different ambient temperatures The determined COP values are used in the simulation model, see Excel file “Simulation model” to calculate the corresponding hourly electricity consumption used for refrigeration in the existing H2O system.


Cycle Illustration

In Figure 4 the supermarket refrigeration cycle with three different ambient temperatures, -20°C, 12.5°C and 30°C, are plotted in a T-s diagram. This T-s diagram and all of the following of this type has been obtained from the software Coolpack, which can be downloaded from [14].

Figure 4: Cycle illustration of CO2 refrigeration system in supermarket where numbers corresponds to nodes in the DNA code

DNA code

TITLE DNA model of a refrigeration circuit H20 network C -------- Input --------- media 400 R744 c Set the baseline for the exergy calculations xergy p 1 t 15 C ------------ Condenser/Gascooler ------------- struc Condenser heatex_6 535 400 171 172 399 100 0.177 0 media 171 SIMPLE_AIR addco q Condenser 399 0 addco p 171 1.01325 addco m Condenser 171 10 addco T Condenser 171 2.5 addco tsat 400 12.5


addco x Condenser 400 0 c Set the desired refrigeration effect [kW] addco q Refri_CoolHX 730 60 c Set the desired refrigeration temperature [C] addco tsat 433 -15 c Set the desired freezing effect [kW] addco q Refri_RefHX 731 20 c Set the desired freezing temperature [C] addco tsat 434 -35 C -------- Split up the liquid flow --------- struc Refri_Split1 splitter 400 430 438 struc Refri_Split2 splitter 430 431 432 C ---------- Cooling ------------ c Defining the throttling valve struc Refri_CoolValve valve_01 431 433 struc Refri_CoolHX heatsrc0 433 530 730 0.061 addco t Refri_CoolHX 530 -10 struc Refri_HPComp COMPRE_1 530 535 331 131 0.71 1 struc Refri_HPCompMotor EL-MOTOR 230 332 131 1 C --------------Refrigeration ------------ c Defining the throttling valve struc Refri_RefValve valve_01 432 434 struc Refri_RefHX heatsrc0 434 531 731 0.061 addco t Refri_RefHX 531 -30 struc Refri_LPComp COMPRE_1 531 532 333 132 0.622 1 struc Refri_LPCompMotor EL-MOTOR 231 334 132 1 struc Refri_GasMix ADDANODE 532 530


START M Condenser 535 0.4099411869849228E+00 {~~} START P 535 0.5414589777778645E+02 {~~} START H Condenser 535 0.5099686649844151E+03 {~~} START M Condenser 400 -0.4099411869849228E+00 {~~} START H Condenser 400 0.2473516181604829E+03 {~~} START M Condenser 171 0.1000000000000000E+02 {~~} START P 171 0.1013250000000000E+01 {~~} START H Condenser 171 -0.1768227044934460E+02 {~~} START M Condenser 172 -0.1000000000000000E+02 {~~} START P 172 0.1013250000000000E+01 {~~} START H Condenser 172 -0.6916516059596818E+01 {~~} START Q Condenser 399 0.0000000000000000E+00 {~~} START ZA Condenser 1 0.1076575438974778E+03 {~~} START ZA Condenser 2 0.3373547792207747E+01 {~~} START M Refri_Split1 400 0.4099411869849228E+00 {~~} START H Refri_Split1 400 0.2473516181604828E+03 {~~} START M Refri_Split1 430 -0.4099411869849228E+00 {~~} START P 430 0.5396889777778645E+02 {~~} START H Refri_Split1 430 0.2473516181604828E+03 {~~} START M Refri_Split1 438 0.0000000000000000E+00 {~~} START P 438 0.5396889777778645E+02 {~~} START H Refri_Split1 438 0.2473516181604828E+03 {~~} START M Refri_Split2 430 0.4099411869849228E+00 {~~} START H Refri_Split2 430 0.2473516181604828E+03 {~~} START M Refri_Split2 431 -0.3069010795244777E+00 {~~} START P 431 0.5396889777778645E+02 {~~} START H Refri_Split2 431 0.2473516181604828E+03 {~~} START M Refri_Split2 432 -0.1030401074604452E+00 {~~} START P 432 0.5396889777778645E+02 {~~} START H Refri_Split2 432 0.2473516181604828E+03 {~~} START M Refri_CoolValve 431 0.3069010795244777E+00 {~~} START H Refri_CoolValve 431 0.2473516181604828E+03 {~~} START M Refri_CoolValve 433 -0.3069010795244777E+00 {~~} START P 433 0.2292890946177666E+02 {~~} START H Refri_CoolValve 433 0.2473516181604828E+03 {~~} START M Refri_CoolHX 433 0.3069010795244777E+00 {~~} START H Refri_CoolHX 433 0.2473516181604828E+03 {~~} START M Refri_CoolHX 530 -0.3069010795244777E+00 {~~} START P 530 0.2286790946177666E+02 {~~} START H Refri_CoolHX 530 0.4428543517871156E+03 {~~} START Q Refri_CoolHX 730 0.6000000000000000E+02 {~~} START M Refri_HPComp 530 0.4099411869849228E+00 {~~} START H Refri_HPComp 530 0.4536943080454574E+03 {~~}


START M Refri_HPComp 535 -0.4099411869849228E+00 {~~} START H Refri_HPComp 535 0.5099686649844150E+03 {~~} START Q Refri_HPComp 331 0.1532990588934907E-14 {~~} START W Refri_HPComp 131 0.2306917668036950E+02 {~~} START E Refri_HPCompMotor 230 0.2306917668036950E+02 {~~} START Q Refri_HPCompMotor 332 -0.1750620497868118E-14 {~~} START W Refri_HPCompMotor 131 -0.2306917668036950E+02 {~~} START M Refri_RefValve 432 0.1030401074604452E+00 {~~} START H Refri_RefValve 432 0.2473516181604828E+03 {~~} START M Refri_RefValve 434 -0.1030401074604452E+00 {~~} START P 434 0.1204830519525319E+02 {~~} START H Refri_RefValve 434 0.2473516181604828E+03 {~~} START M Refri_RefHX 434 0.1030401074604452E+00 {~~} START H Refri_RefHX 434 0.2473516181604828E+03 {~~} START M Refri_RefHX 531 -0.1030401074604452E+00 {~~} START P 531 0.1198730519525319E+02 {~~} START H Refri_RefHX 531 0.4414507946163843E+03 {~~} START Q Refri_RefHX 731 0.2000000000000000E+02 {~~} START M Refri_LPComp 531 0.1030401074604452E+00 {~~} START H Refri_LPComp 531 0.4414507946163843E+03 {~~} START M Refri_LPComp 532 -0.1030401074604452E+00 {~~} START P 532 0.2286790946177666E+02 {~~} START H Refri_LPComp 532 0.4859807095222836E+03 {~~} START Q Refri_LPComp 333 0.3873529465830652E-14 {~~} START W Refri_LPComp 132 0.4588367217108348E+01 {~~} START E Refri_LPCompMotor 231 0.4588367217108348E+01 {~~} START Q Refri_LPCompMotor 334 0.0000000000000000E+00 {~~} START W Refri_LPCompMotor 132 -0.4588367217108348E+01 {~~} START M Refri_GasMix 532 0.1030401074604452E+00 {~~} START H Refri_GasMix 532 0.4859807095222836E+03 {~~} START M Refri_GasMix 530 -0.1030401074604452E+00 {~~} START H Refri_GasMix 530 0.4859807095222836E+03 {~~}


Appendix 7 – Air cooled condenser, Refrigeration cycle in the H2O based system

The screen shot is from the simulation program AIA Calc and shows information regarding the air cooled condenser used in the refrigeration cycle in the H2O based system.


Appendix 8 – Log ph diagrams

NOTE: All log ph diagrams has been found in CoolPack software, which can be found here [14]: CO2 – R744


Propane – R290


R410A


Water – R718


Appendix 9 – CHP Vapor production CO2 based system

Purpose

The purpose of vapor production at the plant side is to fulfill the remaining heat demand after the initial balancing through the synergy effect, by utilizing the excess heat from the CHP production to evaporate CO2 liquid.

System diagram

The system diagram in Figure 5 shows liquid CO2 being evaporated to the vapor CO2 line from the excess heat from the electricity production. Numbers in the diagram is DNA nodes and the DNA model of the heat exchanger can be found at the end of this appendix.

Figure 5: System diagram showing heat exchanger at plant side to produce vapor CO2

Heat exchanger

The condenser at the CHP plant is a direct contact tube condenser, which is commonly used in modern power plants [15]. Water in vacuum is blown over the tubes, which in this case contains liquid CO2. In the process at the warm water hits the tubes, condenses and drops to a hotwell at the bottom, and liquid CO2 at the cold side is evaporated. Pressure losses are not considered on the water side due to the direct contact condenser type, but on the CO2 side pressure losses occur. It is however not of great importance as the pressure difference between the two CO2 pipelines are 5 bar, and an expansion valve is controlling the inlet pressure, to have 40 bar and 8°C at the vapor line outlet. This means a pressure drop of up to 5 bar is allowed in the heat exchanger, and that is assumed not to be an issue.


Results

The most relevant results are shown in Table 8: CO2 evaporating heat exchanger results.

Plant side heat exchanger Unit

�̇� 80 kJ/s Tin CHP 29.8 °C Tin CHP 29.8 °C pCHP 4200 Pa

�̇�CO2 0.28 kg/s

�̇�H2O 0.03 kg/s Table 8: CO2 evaporating heat exchanger results

Due to the very low pressure of the warm vaporized water from the CHP plant, condensation takes place with CO2 as the heat sink. This means the mass flow of water does not need to be high due the considerable amount of latent heat energy available when changing phase.

Cycle illustration

Figure 6: T,s diagram showing illustration of the plant side heat exchanger cycle

Figure 6 shows the heat exchanger cycle in an T,s diagram, where the red curve is the excess heat from the power production, where the power plant run in full condense mode. The black curve shows the liquid CO2 being throttled down and evaporated.


DNA code – Vapor production CHP plant

title Plant side heat exchanger - CO2 vapor production c Defining the throttling valve struc plant_valve valve_01 400 480 media 400 R744 addco T plant_valve 400 8 addco p 400 45 addco p 480 40.1 start m plant_valve 400 0.5 c Defining the heat exchanger struc plant_HEX heatex_1 780 781 480 500 380 0 0.1 media 780 STEAM addco T plant_HEX 500 8 addco q plant_HEX 380 0 start m plant_HEX 780 0.2 addco T plant_HEX 780 29.8 addco T plant_HEX 781 29.7 addco tsat 780 29.8 c Defining the 'heat sink' struc plant_HSI heatsrc0 781 782 381 0.001 addco q plant_HSI 381 80 c Defining the loop pump struc Plant_pump liqpum_1 782 780 201 0.95 start e Plant_pump 201 5


Appendix 10 – Comfort Cooling CO2 based system

Purpose

In supermarkets, malls, shops and office buildings heat emitting sources such as humans, appliances, lighting and solar irradiation make the temperature rise in the rooms and creates a need for comfort cooling to maintain a comfortable temperature. The CO2 system is able to provide the needed comfort cooling very efficient and easy, as CO2 liquid can be throttled down, evaporated and returned to the vapor line without use of any additional machinery than a heat exchanger. Since the liquid line has a higher pressure than the vapor line a natural flow will occur through the heat exchanger.

System diagram

In the following section the system diagram is shown in Figure 7 with DNA nodes. The DNA code can be found in end of this appendix.

Figure 7: System diagram of comfort cooling loop with nodes used in DNA code

Heat exchanger

The heat exchanger used in the comfort cooling cycle is a brazed plate heat exchanger. Data of this type has been obtained from Alfa Laval, based on operating conditions provided to them. The full data sheets can be seen in Appendix 11. The most important result derived from the data sheet was the pressure drop on both sides as these were to serve as input to the DNA file. Obtained pressure drops can be seen in Table 9

CC - heat exchanger Unit

Hot side Cold side Media H2O CO2 Δp 0.113 0.0611 Bar

Table 9: Pressure drops on both sides in the comfort cooling heat exchanger


Results

In the following Table 10 the main results of the CC cycle are shown.

CC cycle Unit

Media H2O Tin 18 °C Tout 10 °C

�̇� 80 kW

�̇�CO2 0.38 kg/s

�̇�H2O 2.42 kg/s Table 10: Results of the CC cycle

It can be noted from Table 10 that the mass flow of water is remarkable higher than the CO2. The reason is that the enthalpy change from evaporating CO2 compared to cooling water is much higher and proportional to the mass flow ratio.

Cycle illustration

Figure 8: T,s diagram of CO2 showing water being cooled from 18°C to 10°C

In Figure 8, a T,s diagram of CO2 is shown. The black curve represents liquid CO2 being evaporated from the liquid supply line to the vapor line. The blue curve represents water being cooled from 18°C to 10°C.


DNA code – Comfort cooling cycle CO2 based system

TITLE Comfort Cooling cycle CO2 based system C Defining the expansion valve struc CC_Valve valve_01 400 440 media 400 R744 addco p 400 45 addco t CC_Valve 400 8 C Defining the heat exchanger struc CC_HX heatex_1 741 742 440 500 340 0.12 0.06 addco q CC_HX 340 0 start m CC_HX 440 0.38 addco t CC_HX 500 8 addco p 500 40 C Defing the water cooling loop struc CC_HouseCooling heatsrc0 742 740 904 5 media 742 STEAM addco p 740 1 start m CC_HouseCooling 742 1 addco t CC_HouseCooling 740 18 addco t CC_HouseCooling 742 10 c Set the needed aircondition effect [kW] addco q CC_HouseCooling 904 80 C Defining the circulation pump in the water loop struc CC_circPump liqpum_1 740 741 240 0.9


Appendix 11 – Refrigeration in CO2 based system

Purpose

The current standard way of obtaining refrigeration is to use electrically driven compression cycles, condensing the refrigerant outside in forced convection air condensers, thereby loosing the produced surplus energy. This leads to a range of less than optimal circumstances, the main one being that the efficiency of the system can be heavily decreased in case of hot weather, which corresponds to the time where a high refrigeration requirements are present.

In the proposed system, the thermal energy being extracted from the refrigerated areas are stored as latent energy in the CO2 system’s vapor line, which has the added benefit that the efficiency of the cycle is not directly dependent on the outside conditions.

System diagram

The proposed cycle is almost the same as explained in section Appendix 6 – Refrigeration H2O system, the main difference being that the outside air cooled condenser has been replaced with connection to the CO2 network. The system diagram is shown with DNA nodes, and the program code can be found at the end of Appendix 11.

Figure 9: System diagram of refrigeration cycle in the CO2 based system

Evaporators

The evaporators in this units is assumed placed directly inside the refrigerated display cases meaning that the energy exchange is from refrigerant to the surrounding air. To achieve the desired display case temperature the pressure is throttled down to approximately 23 bar and 12 bar for the -15⁰C and -35⁰C temperature needs respectively, see Appendix 8 for log ph diagram. The evaporators initially evaporate the CO2, and afterward supply a 5K superheat before releasing the gas to the compressors.


The pressure loss in the evaporators is assumed to be similar to the one obtained for the air condition unit because it has been impossible to obtain actual datasheets for these conditions, and in addition the air condition unit also includes internal evaporation making the units similar.

To ensure that this approximation does not drastically affect the results of the simulations a sensitivity analysis is performed, where the simulations are run using a range of pressure drops for all of the 3 flows through evaporators, whereas the CO2 flow to the network that is merely cooled is assumed to have the same pressure drop that has been obtained for the gas cooler, see Appendix 14 for specifications. The results can be seen in Figure 10 below.

Figure 10: Illustration of the effect of varying pressure drops through the evaporators

In the figure it is evident that the pressure drop can potentially affect the simulation results drastically. However when considering that the obtained pressure drop, while transferring the same flow through a single evaporator which is in this case divided into two, is 0.06 bar, see Appendix 12. It seems highly unlikely that the decreased temperature and pressure in this situation would result in pressure drops in excess of 0.5 bar, which would result in less than 5% decrease in COP compared to 0 bar pressure drop situation.

As a result of the sensitivity analysis, the 0.06 bar pressure drop will be utilized in the simulations, since it is very unlikely that a more accurate value will produce noticeably more accurate results in the final comparison.

Compressors

In this setup two compressors are connected in series, to allow for two different refrigeration temperatures. The low pressure compressor (LP) delivers 20kW of refrigeration at -35°C, after which the CO2 stream is mixed with the -10°C superheated CO2 from the high pressure evaporator delivering 60kW of -15°C refrigeration and then pressurized to the correct vapor supply line pressure in the high pressure compressor (HP).

-25.00

-20.00

-15.00

-10.00

-5.00

0.00

3.50

3.70

3.90

4.10

4.30

4.50

4.70

4.90

0 0.5 1 1.5 2 2.5 3

%COP

Pressure Drop [bar]COP Percent decrease Poly. (COP)


The distribution of 60kW -15°C and 20 kW -35°C refrigeration is based on values from existing supermarket refrigeration systems [12] and is assumed to be representative.

Based on the method described in section 0 two compressors are chosen, resulting in the following values.

Compressor selection Unit

Stage LP HP Producent Bitzer Bitzer Type 2CLS-6K-40S 4VSL-15K-40P Tevap -35 -15 °C Tcond -15 5.3 °C Tsup 5 5 K ηis 0.6972 0.71

Table 11: Compressor specifications

Internal Heat Exchanger

The compressor output temperature when ready to release the vapor to the network is 48.3°C, which would increase the temperature in the pipes and potentially destabilize other equipment connected close by drastically changing the input temperature. To avoid this, an internal heat exchanger is connected, which cools the output vapor by direct evaporation of CO2 liquid to the vapor line. Using this technique the output temperature from the refrigeration system can be adjusted to an appropriate level.

Results

Based on the mentioned considerations, the refrigeration system has been modeled in DNA, resulting in the following values.

Refrigeration cycle LP HP Units Tevap -35 -15 °C Tsuc -30 -1.1 °C Tout 28.21 48.19 °C

�̇� 20 60 kJ/s

�̇�CO2 0.09 0.36 kg/s W 4.02 12.78 kW COP 4.98 4.69 Overall COP 4.76

Table 12: Final refrigeration cycle results Cycle Illustration

In Figure 11 the refrigeration cycle, consisting of a cooling and freezing cycle, is illustrated in a Ts diagram. The green line represents the cooling cycle and the light blue represents the freezing cycle.


Figure 11: Cycle representation of the refrigeration cycle in a T, s diagram.

DNA CODE

TITLE DNA model of a refrigeration circuit CO2 network C -------- Input --------- media 400 R744 addco p 400 45 addco T Refri_Split1 400 8 c Set the baseline for the exergy calculations xergy p 1 t 15 c Set the desired refrigeration effect [kW] addco q Refri_CoolHX 730 60 c Set the desired refrigeration temperature [C] addco tsat 433 -15 c Set the desired freezing effect [kW] addco q Refri_RefHX 731 20 c Set the desired freezing temperature [C] addco tsat 434 -35 C -------- Split up the liquid flow --------- struc Refri_Split1 splitter 400 430 438


struc Refri_Split2 splitter 430 431 432 C ---------- Cooling ------------ c Defining the throttling valve struc Refri_CoolValve valve_01 431 433 struc Refri_CoolHX heatsrc0 433 530 730 0.061 addco t Refri_CoolHX 530 -10 struc Refri_HPComp COMPRE_1 530 535 331 131 0.71 1 struc Refri_HPCompMotor EL-MOTOR 230 332 131 1 C --------------Refrigeration ------------ c Defining the throttling valve struc Refri_RefValve valve_01 432 434 struc Refri_RefHX heatsrc0 434 531 731 0.061 addco t Refri_RefHX 531 -30 struc Refri_LPComp COMPRE_1 531 532 333 132 0.622 1 struc Refri_LPCompMotor EL-MOTOR 231 334 132 1 struc Refri_GasMix ADDANODE 532 530 C --------------- Output gascooler before network -------------- struc Refri_GasCool heatex_6 535 536 439 501 335 10 0.177 0.061 addco q Refri_GasCool 335 0 struc Refri_LiqValve valve_01 438 439 start M Refri_LiqValve 439 1 C Option 1 - Working but not optimal since output is not summed addco t Refri_GasCool 501 8 addco t Refri_GasCool 536 8


addco P 536 40 addco P 501 40 C Option 2 - Not working (trying to collect output) { struc Refri_OutputGasMix1 ADDANODE 501 500 struc Refri_OutputGasMix2 ADDANODE 536 500 c start t Refri_GasCool 501 8 c start t Refri_GasCool 536 7 c addco t Refri_OutputGasMix2 500 8 start t Refri_OutputGasMix2 500 8 addco p 500 40 } C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ C ~~ Start of list of generated initial guesses. C ~~ The values are the results of the latest simulation. C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ START M Refri_Split1 400 0.3741235145072433E+00 {~~} START P 400 0.5500000000000000E+02 {~~} START H Refri_Split1 400 0.2197147972531289E+03 {~~} START M Refri_Split2 431 -0.2389319584630034E+00 {~~} START P 431 0.5500000000000000E+02 {~~} START H Refri_Split2 431 0.2197147972531289E+03 {~~} START M Refri_Split2 432 -0.1351915560442399E+00 {~~} START P 432 0.5500000000000000E+02 {~~} START H Refri_Split2 432 0.2197147972531289E+03 {~~} START M Refri_CoolValve 431 0.2389319584630034E+00 {~~} START H Refri_CoolValve 431 0.2197147972531288E+03 {~~} START M Refri_CoolValve 433 -0.2389319584630034E+00 {~~} START P 433 0.2300000000000000E+02 {~~} START H Refri_CoolValve 433 0.2197147972531288E+03 {~~} START M Refri_CoolHX 433 0.2389319584630034E+00 {~~} START H Refri_CoolHX 433 0.2197147972531288E+03 {~~} START M Refri_CoolHX 530 -0.2389319584630034E+00 {~~} START P 530 0.2290000000000000E+02 {~~} START H Refri_CoolHX 530 0.4427908576632436E+03 {~~} START Q Refri_CoolHX 730 0.5330000000000000E+02 {~~} START M Refri_HPComp 530 0.3741235145072433E+00 {~~}


START H Refri_HPComp 530 0.4583794281402958E+03 {~~} START M Refri_HPComp 535 -0.3741235145072433E+00 {~~} START P 535 0.4290000000000000E+02 {~~} START H Refri_HPComp 535 0.5042629596426597E+03 {~~} START Q Refri_HPComp 331 -0.9034793717719929E+00 {~~} START W Refri_HPComp 131 0.1806958743544018E+02 {~~} START E Refri_HPCompMotor 230 0.1902061835309492E+02 {~~} START Q Refri_HPCompMotor 332 -0.9510309176547424E+00 {~~} START W Refri_HPCompMotor 131 -0.1806958743544018E+02 {~~} START M Refri_RefValve 432 0.1351915560442399E+00 {~~} START H Refri_RefValve 432 0.2197147972531289E+03 {~~} START M Refri_RefValve 434 -0.1351915560442399E+00 {~~} START P 434 0.1200000000000000E+02 {~~} START H Refri_RefValve 434 0.2197147972531289E+03 {~~} START M Refri_RefHX 434 0.1351915560442399E+00 {~~} START H Refri_RefHX 434 0.2197147972531289E+03 {~~} START M Refri_RefHX 531 -0.1351915560442399E+00 {~~} START P 531 0.1190000000000000E+02 {~~} START H Refri_RefHX 531 0.4416221476662186E+03 {~~} START Q Refri_RefHX 731 0.3000000000000000E+02 {~~} START M Refri_LPComp 531 0.1351915560442399E+00 {~~} START H Refri_LPComp 531 0.4416221476662186E+03 {~~} START M Refri_LPComp 532 -0.1351915560442399E+00 {~~} START P 532 0.2290000000000000E+02 {~~} START H Refri_LPComp 532 0.4859300221470828E+03 {~~} START Q Refri_LPComp 333 -0.3152658155832055E+00 {~~} START W Refri_LPComp 132 0.6305316311664106E+01 {~~} START E Refri_LPCompMotor 231 0.6637175064909584E+01 {~~} START Q Refri_LPCompMotor 334 -0.3318587532454781E+00 {~~} START W Refri_LPCompMotor 132 -0.6305316311664106E+01 {~~} START M Refri_GasMix 532 0.1351915560442399E+00 {~~} START H Refri_GasMix 532 0.4859300221470828E+03 {~~} START M Refri_GasMix 530 -0.1351915560442399E+00 {~~} START H Refri_GasMix 530 0.4859300221470828E+03 {~~} C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ C ~~ End of generated initial guesses. C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


Appendix 12 – CO2 heat exchanger from Alfa Laval

Brazed Plate Heat Exchanger Technical Specification Model : CBXP52-150H(32870 9373 5) ItemName : CO2 Fordamper Dato : 06-06-2011 Enheder : 1 ___________________________________________________________________________________ Hot Side Cold side Secondary side Primary side(S4) Væske Water Carbon dioxide Mass flow rate kg/s 1.935 0.3129 Fluid Condensed/Vapourized kg/s 0.000 0.3129 Inlet temperature °C 18.0 8.1 Dew p. °C 8.0 Outlet temperature(vapor/liquid) °C 10.0 9.0 Operating pressure(In/Out) bara / 43.0/42.9 Pressure drop kPa 11.3 6.11 Velocity connection(In/Out) m/s 2.74/2.74 0.930/6.32 Heat Exchanged kW 65.00 Heat transfer area m² 7.55 O.H.T.C clean conditions W/(m²*K) 2358 O.H.T.C service W/(m²*K) 2220 Fouling resistance*10000 m²*K/W 0.0 Margin % 6.23 Mean Temperature Difference K 3.9 Relative directions of fluids Countercurrent Number of passes 1 1 Materialplate/ brazing Alloy 316 / Cu TilslutningS1 (Hot-In) Threaded (External)/ 1"1/4 ISO 228/1-G (B32) Alloy 316 TilslutningS2 (Hot-Out) Threaded (External)/ 1"1/4 ISO 228/1-G (B32) Alloy 316 TilslutningS3 (Cold-In) Sold for Distributor/ 1 1/8" (Q21) Alloy 316 TilslutningS4 (Cold-Out) Soldering/ 1-1/8" (H21) Alloy 316 Pressure vessel code PED Design pressure at 90.0 Celsius Bar 90.0 90.0 Design pressure at 225.0 Celsius Bar 75.0 75.0 Design temperature °C -196.0/225.0 Overall length x width x height mm 393 x 111 x 526 Net weight, empty / operating kg 36.9 / 36.9 Package length x width x height mm 470 x 125 x 579 Package weight kg 0.8000 Price RCPL incl Extras -Unit 32870 9373 5 ___________________________________________________________________________________ Performance is conditioned on the accuracyof customers data and customers abilityto supply equipment and products in conformity therewith.


Physical Properties ___________________________________________________________________________________ Hot Side Cold side (inlet/outlet) Liquid Vapour Liquid Vapour Dens 998.0/1000 861.5/855.0 120.7/119.0 Sp.heat 4.193/4.204 3.409/3.469 2.375/2.268 Visc 1.06/1.31 0.0934/0.0918 0.0184/0.0186 Th.Cond 0.600/0.587 0.0979/0.0962 0.0179/0.0181 Bub. p. /8.0 Dew p. /8.0 Mol.W. 44.01/44.01 Cr.pr. 73.77/73.77 Cr.Temp. 31.0/31.0 Lat.heat 205.5/202.1


Appendix 13 – Open Loop Domestic Hot Water – OLDHW

The following sections briefly present the main aspects, but a description including cycle components can be found in Appendix 13.

Purpose

The purpose of the Open Loop Domestic Hot Water (OLDHW) heat pump is to supply consumers with hot water, both for space heating (SH) and domestic hot water (DHW) purposes. These two purposes are very similar, but there is a very crucial difference which must be considered when simulating the system. The DHW consumption is considered heated from an ambient ground temperature assumed to be 8⁰C, whereas the SH has a return loop from the building, meaning that the space heating is only heated from an assumed return temperature of 40⁰C [16]. In large building complexes the DHW is also circulated, but as a simplification the circulation pipes are assumed to be insulated adequately to eliminate excessive heat loss, meaning that only the consumed water must be heated.

System diagram

There are two different system varieties considered, one using an expander which could possibly increase the systems COP, and another more standard cycle utilizing a valve to decrease pressure.

Figure 12: Refrigeration system schematics for the CO2 system, one with expander and another with valve implemented, the numbers correspond to nodes in the DNA file.

Internal heat exchanger

Since the CO2 vapor in the network is very close to the saturation point, an internal heat exchanger is used to transfer energy from the output of the gascooler to the input for the compressor, thereby ensuring an additional superheat of 5K.

Compressor

The compressor is responsible for increasing the pressure and temperature of the gas to the desired level. To simulate the compressor in DNA, an isentropic and mechanical efficiency must be set.


The isentropic efficiency is determined based on a method obtained from [17], where:

𝑃�� =𝑃��𝑃��

𝜂�� = 𝑎1 + 𝑎2 ∙ 𝑃�� + 𝑎3 ∙ 𝑃��.� + 𝑎4 ∙ 𝑃�� + 𝑎5 ∙ 𝑃��.�

Where:

𝑎1 = 4.39004614408 𝑎2 = −3.5085777881 𝑎3 = 1.5130806248

𝑎4 = −0.0236297366209 𝑎5 = −2.31968952362

Running this algorithm results in an isentropic efficiency (ηis), which is then used in the cycle calculations in DNA leading to a new output pressure (Pout) and temperature (Tout)since the change in efficiency changes the temperature/pressure correlation of the compressors output. After a few iterative calculations, the final compressor isentropic efficiency and thereby corresponding output pressure and temperature is determined for both DHW and SH production.

ηis Pout Tout [-] [bar] [⁰C] DHW 0.646 86.93 85 SH 0.643 100.73 100

The mechanical efficiency is used in DNA to calculate the thermal losses from the compressor to the surroundings, mainly arising from the friction at shaft entry. In this case, a semi hermetic compressor has been chosen, meaning that the motor is integrated into the compressor housing and is cooled by the refrigerant flowing by. Therefore no mechanical motion is transferred through the compressor shell and all heat loss is assumed transferred to the refrigerant, leading to a situation where the mechanical loss is actually included in the isentropic efficiency previously determined and is therefore set to 100%. The same is true for the electric motor used to drive the compressor, which is also integrated into the compressor housing, meaning that the calculated isentropic efficiency also includes these losses, meaning that the electrical motors efficiency must also be set to 100%.

Gas cooler

The gas cooler heats water by transferring energy from the hot CO2 stream to the cold water stream in a counter flow setup, thereby utilizing the very similar temperature glide of the two components to ensure a favorable heat transfer throughout the heat exchanger.

A brazed plate heat exchanger, APX 52.114L from Alfa Laval, see Appendix 14, is used to obtain the needed inputs for DNA as well as providing a reasonable size for a single unit, these value can be seen in Table 13 below where the system has been optimized according to the two different water temperature inputs.


Alfa Laval APX 52.114L DHW SH �̇� [kJ/s] 80 80 Unit H2O side CO2 side H2O side CO2 side �̇� [kg/s] 0.37 0.31 0.96 0.26 Tin [⁰C] 8 85 40 100 Tout [⁰C] 60 18 60 41 ΔP [bar] 0.110 0.177 0.587 0.274

Table 13: Gas cooler specifications Valve or Expander

One way of improving the efficiency of a heat pump is to recapture some of the energy wasted when simply using a throttling valve to achieve the desired evaporation pressure. This approach is currently under research and could potentially become available for commercial use in a few years, making it an interesting point to include. However when doing so the increased complexity of the heat pump and resulting increased risk of failure must be considered. To assess this, the cycle has been simulated both with an expander and a simple valve, the results are illustrated in Table 14 below.

DHW SH

ηexp �̇� W COP Improvement W COP Improvement

[%] [kJ/s] [kW] [-] [%] [kW] [-] [%] Valve 0 80 15.98 5.01 0.00 26.90 2.97 0.00 Expander 30 80 15.54 5.15 2.83 25.48 3.14 5.57 Expander 45 80 15.31 5.23 4.38 24.77 3.23 8.60 Expander 60 80 15.09 5.30 5.90 24.06 3.33 11.80 Expander 75 80 14.86 5.38 7.54 23.35 3.43 15.20 Expander 90 80 14.64 5.46 9.15 22.63 3.54 18.87 Table 14: Expander efficiency changed (Present = 0.45)

As is seen in the table the efficiency gain is noticeable, depending on the efficiency of the expander. Literature [18] indicates that an expander efficiency of 45% is obtainable, meaning that an improvement of 4.38% and 8.6% respectively on the COP of the system can be realized when comparing to the system with a valve.

However based on the facts that the expander is not actually commercially available and the potential gains are relatively small compared with the increased complexity and potentially increased risk of failure, the version using a simple valve will be utilized in the rest of the simulations.


Separator tank

There are a number of possible ways to ensure that the heat pump only releases pure liquid back to the liquid supply line, two of which are the easiest.

1. To incorporate a separator tank that releases gas back to the compressor and liquid to the network. 2. By ensuring that the output temperature from the internal heat exchanger is lower than the 10°C

evaporation temperature of CO2 at the 45bar of the network.

Both of these approaches have positive and negative sides. The separator tank would add to the price of the heat pump, but on the other hand it is a much simpler solution with regard to control during fluctuations in demand on the consumer side, where the mass flow might change quickly. From a network point of view, this solution has the advantage that when a large number of separator tanks are distributed throughout the system, they will help to balance fluctuations in demand by functioning as buffer capacity.

On the other hand, the possibility of simply ensuring a low enough output temperature from the heat exchanger before the valve, promises a cheaper solution because of the smaller number of parts. However if this is to be achieved the temperature difference in the heat exchanger must be below 2°C, since the network gas has an input temperature of 8⁰C and the output temperature must be below 10°C. This would lead to en increased price for the heat exchanger and potential problems with regard to control during sudden changes in demand on the consumer side.

Based on the possibility of increased system stability, the final choice for the simulations is the solution with a separator tank.

Results

The final results are presented in Table 15 below.

Open loop cycle 8°C -60°C 40°C -60°C Units Tcomp out 85 100 °C Tsup 8 8 K Tliq 10 10 °C

�̇� 80 80 kJ/s

�̇�CO2 0.32 0.26 kg/s

�̇�H2O 0.37 0.96 kg/s

W 16 26.63 kW COP 5 3 -

Table 15: Final cycle results for the OLDHW unit As can be seen, the CO2 system benefits heavily from low return temperatures, meaning that this setup is primarily suited for DHW production, while still performing adequately in regard to SH.


Cycle Illustration

The final cycles are illustrated below, where the black line is the CO2 cycle and the blue is the water being heated. In the current simulations the lowest temperature difference is 4⁰C and 1⁰C for DHW and SH respectively.



DNA Code

TITLE Open Loop Domestic Hot Water - Valve and separatortank c Set state in Network addco t OLDHW_GasMix 500 8 c addco x OLDHW_GasMix 500 1 c addco h OLDHW_GasMix 500 430 addco p 500 40 addco p 400 45


media 501 R744 media 801 STEAM addco p 801 3 c Set the baseline for the exergy calculations xergy p 1 t 15 { C Optimized for T_ret = 8C c Set the needed heating effect [kW] addco q OLDHW_Consumption 901 -80 c Set the desired hot water temperature addco t OLDHW_GasCool 802 60 c Set the cold water inlet temperature addco t OLDHW_GasCool 801 8 c Set the compressor CO2 output temperature c addco t OLDHW_Comp 503 85 c Set the gas cooler CO2 output temperature addco t OLDHW_GasCool 504 18 c Superheat - Compressor input temperature addco t OLDHW_IntHX 502 13 c Gascooler inset here due to varying pressure drops struc OLDHW_GasCool heatex_6 503 504 801 802 303 100 0.177 0.110 addco q OLDHW_GasCool 303 0 struc OLDHW_IntHX heatex_1 504 505 501 502 301 0.177 0.177 addco q OLDHW_IntHX 301 0 C COMPRE_1 Input Output HeatLoss ShaftPower IsentroEff MechEff struc OLDHW_Comp COMPRE_1 502 503 302 101 0.646 1 } C Optimized for T_ret = 40C c Set the needed heating effect [kW] addco q OLDHW_Consumption 901 -80 c Set the desired hot water temperature addco t OLDHW_GasCool 802 60


c Set the cold water inlet temperature addco t OLDHW_GasCool 801 40 c Set the compressor CO2 output temperature addco t OLDHW_Comp 503 100 c Set the gas cooler CO2 output temperature addco t OLDHW_GasCool 504 41 c Superheat - Compressor input temperature addco t OLDHW_IntHX 502 13 c Gascooler inset here due to varying pressure drops struc OLDHW_GasCool heatex_6 503 504 801 802 303 100 0.274 0.587 addco q OLDHW_GasCool 303 0 struc OLDHW_IntHX heatex_1 504 505 501 502 301 0.274 0.274 addco q OLDHW_IntHX 301 0 C COMPRE_1 Input Output HeatLoss ShaftPower IsentroEff MechEff struc OLDHW_Comp COMPRE_1 502 503 302 101 0.6433 1 c ~~~~~~~~~~~~~~~~~~~~~~~~ Programming ~~~~~~~~~~~~~~~~~~~~~~~~ struc OLDHW_CircPump liqpum_1 802 803 201 0.9 struc OLDHW_Consumption heatsnk0 803 801 901 0.5 struc OLDHW_Valve valve_01 505 506 c struc OLDHW_Expan TURBIN_1 505 506 101 0.45 addco p 506 45 C EL-MOTOR EL-Input HeatLoss ShaftPower MechEff struc OLDHW_CompMotor EL-MOTOR 202 304 101 1 C Separator tank Input GasOut LiquidOut STRUC OLDHW_Sepa LIQSEP_1 506 507 401 struc OLDHW_LiqValve valve_01 401 400 struc OLDHW_GasValve valve_01 507 501 struc OLDHW_GasMix ADDANODE 500 501


C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ C ~~ Start of list of generated initial guesses. C ~~ The values are the results of the latest simulation. C ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ START M OLDHW_CircPump 802 0.3829413993772187E+00 {~~} START P 802 0.3000000000000005E+01 {~~} START H OLDHW_CircPump 802 0.2513895844284833E+03 {~~} START M OLDHW_CircPump 803 -0.3829413993772187E+00 {~~} START P 803 0.3537000000000006E+01 {~~} START H OLDHW_CircPump 803 0.2514502647574515E+03 {~~} START E OLDHW_CircPump 201 0.2323701008976800E-01 {~~} START M OLDHW_Consumption 803 0.3829413993772187E+00 {~~} START H OLDHW_Consumption 803 0.2514502647574515E+03 {~~} START M OLDHW_Consumption 801 -0.3829413993772187E+00 {~~} START P 801 0.3037000000000005E+01 {~~} START H OLDHW_Consumption 801 0.3392350965739738E+02 {~~} START Q OLDHW_Consumption 901 -0.8E+02 {~~} START M OLDHW_GasCool 503 0.3500136362063624E+00 {~~} START P 503 0.8515438421582358E+02 {~~} START H OLDHW_GasCool 503 0.4777002871975614E+03 {~~} START M OLDHW_GasCool 504 -0.3500136362063624E+00 {~~} START P 504 0.8501138421582358E+02 {~~} START H OLDHW_GasCool 504 0.2397759483274841E+03 {~~} START M OLDHW_GasCool 801 0.3829413993772187E+00 {~~} START H OLDHW_GasCool 801 0.3392350965739738E+02 {~~} START M OLDHW_GasCool 802 -0.3829413993772187E+00 {~~} START H OLDHW_GasCool 802 0.2513895844284833E+03 {~~} START Q OLDHW_GasCool 303 0.0000000000000000E+00 {~~} START ZA OLDHW_GasCool 1 0.8327676298991037E+00 {~~} START ZA OLDHW_GasCool 2 0.7342822687819405E+00 {~~} START M OLDHW_IntHX 504 0.3500136362063624E+00 {~~} START H OLDHW_IntHX 504 0.2397759483274841E+03 {~~} START M OLDHW_IntHX 505 -0.3500136362063624E+00 {~~} START P 505 0.8501138421582358E+02 {~~} START H OLDHW_IntHX 505 0.2296849239271913E+03 {~~} START M OLDHW_IntHX 501 0.3500136362063624E+00 {~~} START P 501 0.4282000000000007E+02 {~~} START H OLDHW_IntHX 501 0.4252071160875033E+03 {~~}


START M OLDHW_IntHX 502 -0.3500136362063624E+00 {~~} START P 502 0.4282000000000007E+02 {~~} START H OLDHW_IntHX 502 0.4352981404877961E+03 {~~} START Q OLDHW_IntHX 301 0.0000000000000000E+00 {~~} START ZA OLDHW_IntHX 1 0.3531996143393568E+01 {~~} START M OLDHW_Comp 502 0.3500136362063624E+00 {~~} START H OLDHW_Comp 502 0.4352981404877961E+03 {~~} START M OLDHW_Comp 503 -0.3500136362063624E+00 {~~} START H OLDHW_Comp 503 0.4777002871975614E+03 {~~} START Q OLDHW_Comp 302 -0.2992395948020072E-14 {~~} START W OLDHW_Comp 101 0.1484132955284054E+02 {~~} START E OLDHW_CompMotor 202 0.1484132955284054E+02 {~~} START Q OLDHW_CompMotor 304 0.0000000000000000E+00 {~~} START W OLDHW_CompMotor 101 -0.1484132955284054E+02 {~~} START M OLDHW_Sepa 506 0.3500136362063624E+00 {~~} START H OLDHW_Sepa 506 0.2296849239271913E+03 {~~} START M OLDHW_Sepa 507 -0.7498739929830487E-02 {~~} START P 507 0.4500000000000008E+02 {~~} START H OLDHW_Sepa 507 0.4233068130802522E+03 {~~} START M OLDHW_Sepa 401 -0.3425148962765319E+00 {~~} START P 401 0.4500000000000008E+02 {~~} START H OLDHW_Sepa 401 0.2254459252521993E+03 {~~} START M OLDHW_LiqValve 401 0.3425148962765319E+00 {~~} START H OLDHW_LiqValve 401 0.2254459252521993E+03 {~~} START M OLDHW_LiqValve 400 -0.3425148962765319E+00 {~~} START P 400 0.4500000000000008E+02 {~~} START H OLDHW_LiqValve 400 0.2254459252521993E+03 {~~} START M OLDHW_GasValve 507 0.7498739929830487E-02 {~~} START H OLDHW_GasValve 507 0.4233068130802522E+03 {~~} START M OLDHW_GasValve 501 -0.7498739929830487E-02 {~~} START H OLDHW_GasValve 501 0.4233068130802522E+03 {~~} START M OLDHW_GasMix 500 0.3425148962765319E+00 {~~} START P 500 0.4282000000000007E+02 {~~} START H OLDHW_GasMix 500 0.4252487197613702E+03 {~~} START M OLDHW_GasMix 501 -0.3425148962765319E+00 {~~} START H OLDHW_GasMix 501 0.4252487197613703E+03 {~~}


Appendix 14 – CO2 gas cooler from Alfa Laval


Appendix 15 – Closed Loop Domestic Hot Water – CLDHW

Purpose

This cycle is called closed loop because it has a closed loop between the CO2 network and the water loop to and from the customers. Some customers need high temperature water or perhaps steam for processes and this can be covered by the use of the closed loop cycle as a refrigerant with subcritical properties in this region of condensing temperature can be utilized. Another purpose of the closed loop, and the only one dealt with in this project, is to supply domestic hot water and space heating. The closed loop is used at times when domestic water returned from the customers is too high leading to small temperature lifts. The efficiency of the open loop quickly drops due to the transcritical behavior, while the subcritical closed loop can maintain a higher efficiency.

System diagram

The system diagram including notes used in DNA is shown in Figure 15 below.

Figure 15: System diagram of closed loop cycle with DNA notes

Refrigerant

There are many different refrigerants able to be working fluid in a closed loop cycle, and in the following section a suitable refrigerant will be chosen based on an investigation of the performance of the system. In Appendix 16, a more elaborate exposition of the considerations behind the choice of refrigerant, can be red.

Due to the European laws on refrigerants, synthetic refrigerants are either illegal to use or is being phased out as these contribute to ozone depletion and/or global warming, except some HFC gasses in small applications [9]. This means the main focus will be on natural refrigerants, though R134A is part of considerations as well.


Calculations of performance have been carried out in DNA, where it assumed the cycle had to heat water from 8°C to 60°C and the results can be seen in Table 16.

Propane Butane Isobutane Propylene Ammonia R134A Units Refrigerant number R290 R600 R600a R1270 R717 R134A Tevap 0 0 0 0 0 0 °C Tcond 53 53 53 53 53 53 °C ΔPcomp 4.1 6.4* 5.4 4.4 5.2 5 Tsup 20 20 20 20 3 3 K Tsub 28 28 28 28 33 33 K Tcomp out 89.5 86.2 81.8 97.9 168.8 73.4 °C �̇� 80.0 80.0 80.0 80.0 80.0 80.0 kW W 18.1 18.8 18.2 18.3 19.8 18.59 kW COP 4.42 4.25 4.39 4.37 4.04 3.99 Table 16: Results of calculations of performance with different refrigerants in a closed loop cycle.

The DNA model used in the calculations for propane, butane, isobutane and propylene, is a bit different as an internal heat exchanger is placed with the hot side after the condenser and cold side before the compressor to achieve 20K superheat, which is needed [19].

Propane has in the end been chosen as the refrigerant in closed loop because of the best performance. The properties of propane makes it flammable, which means special precautions, has to be taken with this type.

Compressor

The compressor is responsible for increasing the pressure and temperature of propane to the desired level. To simulate the compressor in DNA, an isentropic and mechanical efficiency must be set. With propane as the refrigerant, a semi-hermetic reciprocating compressor is chosen, meaning the mechanical efficiency is put to 100%, due to the reasons explained in section 0

Compressors from the German company Bitzer, was chosen for investigation to find the optimal compressor type, as Bitzer software, [11] , was available and able to provide all necessary parameters needed to calculate capacities, efficiencies and displacement volumes.

Propane has very similar properties to R22, which has been banned in Denmark, but is able to use the same compressors. Due to the flammable nature of propane, a special type of R22 compressor from Bitzer is chosen for investigation. The choice has been a semi hermetic reciprocating compressor of the type 6J-33.2P, which is able to fulfill the demand of 80kW.

The isentropic efficiency which is needed in the simulations of the cycle was calculated in EES, see EES file “Compressor selection” using the same 10 unique coefficients as described in section 0. The coefficients obtained are unique for this compressor. The results can be seen in Table 17:


Compressor selection Unit Temp. Water lift 40°C-60°C 8°C-60°C Producent Bitzer Bitzer Type 6J-33.2P 6J-33.2P Refrigerant R290 R290 Tevap 0 0 °C Txond 53 55 °C Tsup 20 40 K Tsub 28 10 K ηis 0.6972 0.7292

Table 17: Compressor results, closed loop cycle.

Internal heat exchanger

An internal heat exchanger is placed in the cycle after the condenser on the hot side and before the compressor on the cold side. The reason for this is that propane needs at least 20K superheat before the compressor to ensure no liquid is present in the gas [19].

Evaporator and condenser

In the closed loop cycle three heat exchangers are part of the cycle, between CO2 network to closed loop, between closed loop and domestic hot water and an internal heat exchanger. It has been impossible to obtain actual data sheets under the given conditions, but the heat exchanger obtained for comfort cooling, will be used in each cases because of the similarity.

The data sheet of the air condition unit has CO2 on one side and water on the other, and since phase changes do not occur at the water side, the pressure drop is different from the CO2 side. The pressure drop is assumed to be the same for propane as for CO2 in the first heat exchanger between the network and the closed loop as both gasses change phase. In the second heat exchanger between the closed loop and the domestic hot water, propane is assumed to have the same pressure drop as CO2 and water will have the same pressure drop as obtained in the data sheet. The internal heat exchanger will have the same pressure drop as the gas cooler in section 0, as the gas is merely cooled/heated with no phase change.

To ensure a drastically pressure drop will not affect the results of the simulations in particular, a sensitivity analysis varying the pressure drops of propane and CO2 in the heat exchangers has been performed. The results can be seen in Figure 16 below:


Figure 16: Results of sensitivity analysis with pressure drop in heat exchangers in closed loop cycle

From the figure it can be seen that pressure drops in evaporator/condenser can have a significant effect on the COP of the cycle, but considering the flow through one heat exchanger the pressure drop is found to be 0.06bar Appendix 12 and a doubling of this is only going to result in a percentage decrease in COP of 1.5%.

As a result of the sensitivity analysis, the pressure drop of 0.06bar will be used at the propane and CO2 sides in the heat exchangers, and pressure drops in the internal heat exchanger will be the same as with the gas cooler in section 0.

Results

The closed loop cycle has been modeled in DNA including relevant input parameters, Table 18 below presents the most relevant results.

Closed Loop Domestic Hot Water cycle 8°C -60°C 40°C -60°C Units Refrigerant Propane Propane Tevap 0 0 °C Tcond 53 55 °C Tsup 20 40 K Tsub 28 10 K �̇� 80 80 kW �̇�CO2 0.27 0.28 kg/s �̇�prop 0.18 0.18 kg/s �̇�H2O 0.37 0.96 kg/s W 18.7 21.38 kW COP 4.28 3.74

Table 18: Results of the closed loop cycle

-35.00

-30.00

-25.00

-20.00

-15.00

-10.00

-5.00

0.00

3.003.203.403.603.804.004.204.404.604.805.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2

%COP

Pressure Drop [bar]COP Percent decrease Poly. (COP)


Cycle Illustration

In Figure 17 and Figure 18 the closed loop cycle is shown in a T,s diagram with the nodes used in DNA. The black curve is the propane cycle, and the blue curve is water being heated from 8°C to 60°C and 40°C to 60°C respectively.



DNA Code


8°C - 60°C

c Model of closed loop heat pump TITLE DNA model of a closed loop heat pump c Defining the heat exchanger between closed loop and CO2 network struc CLDHW_HEX1 heatex_1 500 410 616 610 310 0.0611 0.0611 media 616 R290 media 500 R744 start m CLDHW_HEX1 500 0.5 addco p 500 40 addco T CLDHW_HEX1 500 8 addco T CLDHW_HEX1 410 5 start m CLDHW_HEX1 616 0.5 addco tsat 616 0 addco T CLDHW_HEX1 610 2 addco q CLDHW_HEX1 310 0 c Defining the liquid pump after the heat exchanger to pressurize CO2 struc CLDHW_pump1 liqpum_1 410 411 210 0.95 addco p 411 45 start e CLDHW_pump1 210 5 c Defining an internal HEX to superheat the gas before the compressor struc CLDHW_int_HEX heatex_1 613 614 610 611 312 0.0611 0.0611 addco q CLDHW_int_HEX 312 0 addco T CLDHW_int_HEX 611 20 c Defining the compressor struc CLDHW_comp compre_1 611 612 311 110 .7292 1 start q CLDHW_comp 311 0 addco tsat 612 53 start W CLDHW_comp 110 20 c Defining the second heat exchanger struc CLDHW_HEX2 heatex_1 612 613 712 710 313 0.0611 0.113 media 712 STEAM addco T CLDHW_HEX2 712 8 addco p 712 3 start m CLDHW_HEX2 712 1 addco T CLDHW_HEX2 613 25 addco T CLDHW_HEX2 710 60 addco q CLDHW_HEX2 313 0 c Defining a HEX to heat liquid before network struc CLDHW_HEX3 heatex_1 614 615 411 400 314 0 0 addco q CLDHW_HEX3 314 0 addco T CLDHW_HEX3 400 8 c Defining the heat sink at the consumers


struc CLDHW_HS heatsnk0 710 711 910 0.113 addco q CLDHW_HS 910 -80 c Defining the loop pump struc CLDHW_pump2 liqpum_1 711 712 211 0.95 start e CLDHW_pump2 211 5 c Defining the throttling valve struc CLDHW_valve valve_01 615 616

40°C - 60°C

TITLE DNA model of a closed loop heat pump c Defining the heat exchanger between closed loop and CO2 network struc CLDHW_HEX1 heatex_1 500 410 616 610 310 0.0611 0.0611 media 616 R290 media 500 R744 start m CLDHW_HEX1 500 0.5 addco p 500 40 addco T CLDHW_HEX1 500 8 addco T CLDHW_HEX1 410 5 start m CLDHW_HEX1 616 0.5 addco tsat 616 0 addco T CLDHW_HEX1 610 2 addco q CLDHW_HEX1 310 0 c Defining the liquid pump after the heat exchanger to pressurize CO2 struc CLDHW_pump1 liqpum_1 410 411 210 0.95 addco p 411 45 start e CLDHW_pump1 210 5 c Defining an internal HEX to superheat the gas before the compressor struc CLDHW_int_HEX heatex_1 613 614 610 611 312 0.0611 0.0611 addco q CLDHW_int_HEX 312 0 addco T CLDHW_int_HEX 611 40 c Defining the compressor struc CLDHW_comp compre_1 611 612 311 110 .7292 1 start q CLDHW_comp 311 0 addco tsat 612 55 start W CLDHW_comp 110 20 c Defining the second heat exchanger struc CLDHW_HEX2 heatex_1 612 613 712 710 313 0.0611 0.113 media 712 STEAM addco T CLDHW_HEX2 712 40 addco p 712 3 start m CLDHW_HEX2 712 1 addco T CLDHW_HEX2 613 45


addco T CLDHW_HEX2 710 60 addco q CLDHW_HEX2 313 0 c Defining a HEX to heat liquid before network struc CLDHW_HEX3 heatex_1 614 615 411 400 314 0 0 addco q CLDHW_HEX3 314 0 addco T CLDHW_HEX3 400 8 c Defining the heat sink at the consumers struc CLDHW_HS heatsnk0 710 711 910 0.113 addco q CLDHW_HS 910 -80 c Defining the loop pump struc CLDHW_pump2 liqpum_1 711 712 211 0.95 start e CLDHW_pump2 211 5 c Defining the throttling valve struc CLDHW_valve valve_01 615 616


Appendix 16 – Choice of refrigerant in closed loop cycle

The choice of refrigerant depends on the application in regards to desired condensing and evaporation temperatures and safety issues. To choose the right refrigerant for the closed loop, several criteria are put up to narrow down the choices. The criteria made are:

● Preferably be a natural refrigerant due to laws against the use of many synthetic refrigerants [9].

● Must be able to have high condensing temperatures. ● Must be able to have evaporating temperature below 8°C. ● Have low or no global warming potential and ozone depletion potential. ● Would preferable be in safety group A1

Due to the European laws on refrigerants, synthetic refrigerants are either illegal to use or is being phased out as these contribute to ozone depletion and/or global warming. HFC gasses is still widely used though as there is a limit of 10kg or 50kg (chillers with heat recovery system) of refrigerant in a chiller or heat pump, [9]. The most common HFC refrigerant R134a is chosen to be part of the considerations, though the main focus will be on natural refrigerants.

In the following section the different refrigerants will be discussed and evaluated, in order to find the most suited refrigerant for applications in this study. A table with relevant parameters of the refrigerants considered has been made and can be seen in

Boiling temperature

Critical temperature

Critical pressure

GWP pr. 100 years Safety Group

Unit [°C] [°C] [bar] R170 - Ethane -88.3 32.17 48.72 5.5 A3

R290 - Propane -42.2 96.7 42.48 3.3 A3 R600 - Butane -0.44 152 37.96 4.4 A3

R600a - Isobutane -11.78 134.7 36.4 3 A3 R717 - Ammonia -33.33 132.3 113.3 0 B2

R744 - CO2 -57 31.06 73.86 1 A1 R1270 - Propylene -47.78 92.42 46.65 1.8 A3

R134a - Tetrafluoroethane -26.06 101.08 40.6 1430 A1 Table 19: Relevant properties of possible choices of refrigerant

Natural refrigerants, Methane, R50, Ethane, R170, Nitrogen, R728, Oxygen, R732, Argon, R740 and Ethylene, R1150 are not considered any further as these are transcritical in the temperature region needed and compressors are not made for applications such as water heating. Water is not considered either as it cannot evaporate at 0°C and requires extreme compressor work to achieve the desired condensing temperature. This leaves ammonia, R717, Tetrafluoroethane,R134a, and the hydrocarbons, propane, R290, butane, R600, isobutane, R600a, Propylene, R1270, for further considerations.


Tetrafluoroethane, R134A

This synthetic refrigerant is very similar to the hydrocarbons considered, both in terms of profile and properties. As seen in Table 20, R134A do not show any advantage over the hydrocarbons and even has restriction of use, due to the high GWP. R134a is not seen as a feasible choice compared to the other candidates and is not considered further.

Ammonia

Ammonia has a profile which is able to fulfill the temperature requirement in the evaporator, but problems arise when it comes to the high temperature lift and condensing temperature. From the software from Bitzer, [11], the largest compressor types are limited to 28 bar and condensing temperature of 53°C. The reason for this is that in order to reach a pressure high enough to achieve the desired condensing temperatures of 53°C to heat domestic hot water, the ammonia out of the compressor nears 150°C. Additionally at high temperature lifts cooling of the compressor oil becomes a problem, and it is expensive to include oil cooling, thus ammonia compressors are avoided when dealing when temperature lifts are high.

Hydrocarbons

The suited hydrocarbons, propane, R290, butane, R600, isobutane, R600a, Propylene, R1270 all have similar properties and refrigerant profile. These profiles are narrow and steep, leading to high compressor work to reach feasible condensation temperatures and remarkable losses in the expansion valve in order to reach the evaporation pressure to utilize the CO2 from the network. However, all the hydrocarbon refrigerants is able to fulfill demand, but with some drawbacks. From Table 20, it should be noticed that butane and isobutane have higher pressure ratios than propane and propylene, and butane has additionally an evaporation pressure below atmospheric pressure which is undesired to avoid ambient air in the system. A major drawback of all the hydrocarbons is the flammability, which requires strict safety proportions. Propane Butane Isobutane Propylene Ammonia R134A Units Refrigerant number R290 R600 R600a R1270 R717 R134A Evaporation temp. 0 0 0 0 0 0 °C Condensation temp. 53 53 53 53 53 53 °C Pressure ratio 4.1 6.4* 5.4 4.4 5.2 5 Superheat 20 20 20 20 3 3 K Subcooling 28 28 28 28 33 33 K Compressor output temp. 89.5 86.2 81.8 97.9 168.8 73.4 °C Heat capacity 80.0 80.0 80.0 80.0 80.0 80.0 kW Compressor Elec. Input 18.1 18.8 18.2 18.3 19.8 18.59 kW COP 4.42 4.25 4.39 4.37 4.04 3.99

Table 20: Refrigerant comparison

Propane has in the end been chosen as the refrigerant in closed loop because of the best performance, even though propylene could have chosen as well as this has almost the same properties.


Appendix 17 – Case description and hourly data derivation malls

As a model for the consumption pattern of a mall, consumption values from Fields in Copenhagen are utilized for the comfort cooling, whereas the space heating and hot water consumption is assumed to be similar to that determined for office buildings. The electricity consumption was available because Rambøll already had the data, sadly the heating consumption was not included, and the company which did the measurements has not responded to our requests.

The supplied values for comfort cooling includes the total monthly electricity consumption of the system for 18 months, the daily consumption for two selected months and the hourly distribution of representative days in each of those periods.

To obtain an hourly profile, a series of extrapolations has been made. Initially the monthly consumption is divided with the number of days in the respective month, to obtain average daily electricity consumption. This does not include information about weekends, because the measured daily consumption pattern indicates that it does not significantly influence the consumption. In addition the mall is open on all Saturdays and approximately every other Sunday, meaning that it is only closed for about 2 days each month.

The daily average electricity consumption is then divided with the area of Fields, to obtain the area specific electricity consumption of the cooling system, and then multiplied by an expected COP of 4 to obtain the daily area specific cooling effect needed. Lastly the daily area specific cooling effect is multiplied with the measured hourly distribution, resulting in an hourly area specific cooling effect for an entire year.

A plot of the obtained values can be seen in Table 19 below:

Figure 19: Area specific hourly consumption values for a mall


Appendix 18 – Case description and hourly data derivation of supermarkets

Supermarkets are the only consumer type in this case study which utilizes all four energy services: space heating, hot water, refrigeration and comfort cooling. To estimate the hourly consumption pattern for each of these energy services, data has been provided by Jesper Thorsgaard Larsen (JTL) from the technical department at Dansk Supermarked. The data given is from Føtex in Frederikssund which have a total area of 4461m2 [20]. Unfortunately it was only possible to obtain data for electricity and total heat consumption of:

- Total monthly consumption during a year. (Comfort cooling, total electricity and heat) - Daily consumption in January. (Total electricity and heat) - Hourly consumption for one day each season during the year. (Total electricity and heat)

Additionally the daily consumption data was from January 2011 and the rest of the data was from 2010, which mean that the hourly profile is not the same reference year as the other customer types in this case study. It does make a small difference as the weather in January 2011 is not the same as January 2010 with regard to the weather conditions, which is an important factor to energy consumption. This is not optimal but the consumption of heat and cooling in both years are assumed to be similar enough to be used in the case. The data was given in graphs in PDF format, meaning numbers had to be read of the graphs, leading to some inaccuracies, these graphs can be seen in Appendix 19.

The lack of data means that several assumptions and analysis of the data had to be carried out to make an hourly profile of each of the energy services. Since the data provided only was electricity and heat consumption, the data had to be split into the energy services needed.

Regarding refrigeration consumption JTL estimated that 40% of the total electricity consumption of the supermarket was used for refrigeration purposes, and the compressors had an annual average COP of 3.5.[20]. Monthly electricity consumption to provide comfort cooling was also given, and an estimated annual average COP of 4 for the system was also given [20].

Figure 20: Sequence for constructing an hourly profile of refrigeration from the data and information given.

Splitting up the total heat consumption into hot water and space heating consumption was a bit more difficult, as heat recovery from the refrigeration system was used to preheat the water for cleaning and no information had been provided regarding the distribution of heat for hot water and space heating. The heat supply from the heat recovery is included in the electricity consumption of the refrigeration system. This just leaves a smaller part of the total heat consumption for heating hot water. The distribution was made


by taking a day in mid august which had the lowest possible heat consumption, and assuming that this day was hot enough to have no need for space heating, leaving the total heat consumption to be used to heat water. There is probably an increase in refrigeration consumption due to high ambient temperature and thereby more heat to be recovered and used to preheat the water for cleaning, but this is neglected. The hot water consumption is used for cleaning processes every day, primarily at the butcher and the rest is used at the toilets and other part of the supermarket. It is then assumed that there is a hot water demand of 25 kWh every day of the year, including Sundays.

Figure 21: Sequence for constructing an hourly profile of space heating and hot water from the data and information given.

The hourly consumption profile of space heating, hot water and refrigeration, found in “hourly profile” in Excel sheet “Supermarket” was created by first making a daily consumption profile in January, “Monthly heat consumption in January” from the data given. Each day in January was assigned a percentage corresponding to how much electricity and heat was used that day divided by the total monthly consumption. The daily consumption profile is then assumed to be the profile which the rest of the months also will follow. This however also means that fluctuations in consumptions this month will be repeated every month of the year. The monthly consumption profile was thereby created by multiplying the total monthly consumption found in “Monthly consumption over a year” with the daily profile from January, but with the respect of the weekdays meaning that Mondays are multiplied with Mondays etc. The monthly consumption profiles with consumption of space heating, hot water and refrigeration each day of the year can be found in “Monthly profiles”. Finally, the hourly profiles with consumption of energy services of space heating, hot water and refrigeration were calculated by multiplying the days in the monthly profiles with the hourly distribution of the right season.

Figure 22: Sequence for constructing an hourly profile of comfort cooling from the data and information given.

Comfort cooling was provided as monthly electricity consumption and the comfort cooling produced was found by multiplying the electricity consumption with the COP of 4. To make the hourly distribution a profile of a weekday, a Saturday and a Sunday was made. It was assumed that the supermarket needed comfort cooling in all the opening hours and the hours before opening with a constant demand each hour


throughout the day. The hours with comfort cooling are assumed to be 7-20 at weekdays, 7-18 at Saturday and no consumption on Sundays, because the supermarket is assumed closed. By multiplying each day with the respective daily profile the hourly distribution during a year was made. Every hourly consumption value was in the end divided by the total area of the supermarket, in order to obtain values per m2. The plot of daily profiles per m2 can be seen in Figure 23 below:

Figure 23: Area specific hourly consumption values for a supermarket


Appendix 19 – Obtained data from Føtex in Frederikssund

Comfort Cooling


Electricity Consumption

NOTE: The electricity consumption is of the entire supermarket annually.


NOTE: The electricity consumption is of the entire supermarket monthly.


NOTE: The electricity consumption is of the entire supermarket 4th of February 2011.


Heat consumption

NOTE: Heat consumption is both space heating and hot water from January 2011


NOTE: Heat consumption is both space heating and hot water 4th of February.


Appendix 20 – Case description and hourly data derivation of office buildings

In order to estimate the relevant energy consumption values for office buildings, data from two new low-energy office buildings has been obtained from Rambøll, based on simulations in Integrated Energy Solutions (IES), see Excel file “Office buildings”. These data include both space heating and cooling requirements on an hourly basis, leaving only the hot water demand to be derived.

Figure 24: Sequence for constructing an hourly profile of hot water from the data and information given.

To establish a hot water consumption pattern, the standard consumption value of 100 l/m2/year from Statens Byggeforskningsinstitut’s (SBi) regulation 213, [21], has been utilized. This regulation dictates what energy standards must be satisfied in new buildings, meaning that this value is assumed to be representative for future buildings.

Based on the assumed values stated in Table 21 below, the average daily energy consumption is estimated.

Yearly consumption 100 [l/m2/year] Input temperature 8 [C] Hot water temperature 60 [C] Specific heat capacity 4200 [J/kg-K] Density 1000 [kg/m3] Yearly energy consumption 21840 [kJ/m2/year] Yearly energy consumption 2.49 [kWh/m2/year] Number of work days a year 261 [Workdays/year] Daily energy consumption 0.0095523 [kWh/m2/day]

Table 21: Estimated values for office buildings hot water consumption

As is seen, the number of workdays is assumed to be 261, which is based simply on 5 workdays a week without considering any holidays. This has been chosen in order to simplify the simulations by ensuring relatively steady state operation, which is the most relevant from a system comparison point of view.

To obtain hourly values, the daily consumption is divided equally between the hours from 7 – 17, assuming that the hot water is consumed in the buildings utilization hours.

Based on the two supplied low energy buildings consumption patterns and the estimated hourly hot water consumption, two separate hourly consumption patterns are created based on which, an average is calculated that will form the office consumption pattern utilized in the final case. A plot of the yearly pattern is illustrated in Figure 25 below.


Figure 25: Yearly consumption pattern for office buildings


Appendix 21 – Case description of residential sector

The consumption pattern of space heating and hot water consumption differ considerably when considering it on an hourly basis in residential buildings, thus it is necessary to distinguish between the heat used for space heating and heat used to domestic hot water. In order to do this it is assumed that the space heating demand is relatively constant throughout an entire month with regards to the season and hot water consumption varies every hour throughout the day, but with a constant overall consumption each day. There will not be distinguished between, workdays, weekends and holiday for simplicity reasons, but this will not change the basis for comparison as this is the same for each energy system.

Figure 26: Sequence for constructing an hourly profile of space heating in residential buildings from the data and information given.

Figure 27: Sequence for constructing an hourly profile hot water in residential buildings from the data and information given.

To calculate hourly consumption data, several steps were carried out. Firstly, the data provided showed an almost twice as high heat consumption per square meter in the Høje Søborg II building block when compared to the Værebro building block. This is due to inhabitant density and because Høje Søborg II is older and less isolated [22]. An average heat consumption per square meter was calculated and used. From [21] it is given that from the entire Danish heat consumption in households in 2007, 50 PJ was used for hot water and 113PJ was used for space heating, corresponding to 31% and 69% respectively. To divide the heat consumption between hot water and space heating, it is assumed that these building blocks follow this distribution. To make the hourly space heating consumption profile, the monthly space heating consumption per m2, see Table 22, is divided with the number of hours in the given month. This results in a constant consumption each month. In order to make the hourly hot water consumption profile, a daily consumption pattern has been constructed. The profile can be seen in Figure 28 and has been constructed assuming an hourly percentage of the total daily hot water demand. This profile has then been multiplied with the yearly average hot water consumption per m2, see Table 23.


Average consumption for space heating [kWh/m2]

Year jan feb mar Apr may jun Total 2010 11.68 10.21 8.20 5.56 4.73 2.45 75.55

jul aug sep Oct nov dec 1.76 2.10 3.17 5.78 8.60 11.24

Table 22: Monthly energy consumption for space heating in residential buildings

Average consumption for hot water [kWh/m2] Year jan feb mar Apr may jun Total 2010 2.79 2.79 2.79 2.79 2.79 2.79 20.40

jul aug sep Oct nov dec 2.79 2.79 2.79 2.79 2.79 2.79

Table 23: Monthly energy consumption for hot water in residential buildings

Figure 28: Daily hot water consumption pattern in residential buildings

The hourly consumption patterns of space heating and hot water can be seen in Figure 28. The graph looks a bit odd, but it is due to assumptions made to do the calculations.


Figure 29: Space heating and hot water consumption per m2 in the residential sector.


Appendix 22 – Excel Workbook

In the following chapter, the most important parts of the excel workbook will be presented. To structure the explanations, it will be split into subsections for each sheet in the workbook. Some sheets are hidden in the initial view to assist in creating an overview of the workbook, and thereby prevent it from getting overly chaotic. These can be found by right-clicking on the sheets in the bottom at choosing “Unhide”. In the following they will be marked by having [Hidden] in the heading.

Input

The input sheet contains all the variables needed to construct different scenarios, meaning that all calculations in the workbook refer to these inputs. This has been done to make it as simple as possible to construct different scenarios. At the bottom of the sheet, the resulting total yearly coal consumption of each system is presented, making it fast to determine the effects of the implemented changes.

In addition some of the most central scenarios have their inputs listed next to the actual input column, to make it as easy as possible to recreate or expand the presented scenarios.

Plots

In the Plots sheet, the most important outputs are presented with hourly plot for the entire simulated year.

BalancingPlots

The Balancing plots sheet contain plots of how the systems balance production and consumption throughput the year, indicating how stable the constructed energy system is.

Mall, Residential, Supermarket and OfficeBuilding [Hidden]

In these sheets, the consumption values for each of the building type is represented, forming the background for the FinalData sheet where they are all added together.

ThermalData and CHP-Plot

In these sheets, all the data for the CHP production is presented, including storage and fuel information. The most important values are the electricity to power ratio and the electrical efficiency of the plant, since these play a central part in determining the relationship between electricity and district heating production and the resulting coal consumption.

ElectricityData2010

This sheet contains actual production data from wind turbines and electricity consumption data from 2010, divided into the eastern and western Denmark. Based on these values and the variable inputs from the input sheet, the simulated production from non-thermal electricity sources are calculated on an hourly basis, which will later be utilized to determine the remaining electricity demand that must be satisfied from thermal production sources.


SeaTemperature – [Hidden]

This sheet contains measured sea temperatures from 2009, measured at the bottom close to the island Ven located close to Copenhagen. To simplify the further calculations, each temperature is rounded off to the nearest integer, leaving five temperature steps from 8⁰C to 12⁰C based on which the COP of the CO2 systems sea based balancing measures will later be determined.

CopenhagenRefYear – [Hidden]

This sheet contains values for solar irradiance, temperature and relative air humidity for a reference year in Copenhagen. This data has been obtained from [23], and is used to distribute the renewable production from solar sources as well as dividing the hourly temperatures into 11 discrete temperature steps for each of which a COP is determined, for both the comfort cooling and refrigeration cycles in the H2O system. This information is used to determine the electricity needed to supply the required levels of cooling and refrigeration for each hour.

Final Data

This is the primary calculation sheet with regard to determining the demands of the constructed case. Initially the contribution to the overall system demand from each of the four building types is determined for each of the four different thermal energy types. This is done by first multiplying the total chosen area with the building type’s percentage of the total, and then finally multiplying that with the building type’s specific use of energy per m2. An example of this calculation can be seen below for the residential sectors contribution to the total SH demand

𝑄�� = 𝐴�� · 𝛷�� · 𝑞��

Then all of the contributions are added together to determine the total consumption of each energy service in the simulated area.

Afterwards the electricity consumption is calculated based on the actual consumption data for the eastern region in 2010, by first determining the amount of electricity for the entire Copenhagen area and then multiplying with the percentage of the Copenhagen area that is simulated.

𝑃�� = 𝑃�� ·𝑁��𝑁��

·𝐴��𝐴��

This is considered to be the power demand for the H2O based system, however because the two systems deliver refrigeration services with different efficiencies, the electricity consumption must be split up into non-thermal electricity demand and electricity demand for thermal uses. To do this, the electricity consumption for refrigeration and comfort cooling is determined based on the efficiencies determined for the H2O system, and then subtracted from the total power consumption, leaving the non-thermal electricity demand.

As a final step, the electricity production from non-thermal sources, determined in sheet “ElectricityData2010”, are subtracted from the non-thermal electricity demand, to obtain the amount of non-thermal electricity demand that the two systems must supply from thermal CHP production. It should


be noticed that in case the electricity production from non-thermal sources exceed the demand from non-thermal sources this value will be negative, indicating that there is an excess of electricity in the system.

Plot-Consumption

The Plot-Consumption sheet simply contains a plot of the total consumption of each of the four thermal sources and electricity, that each of the energy systems will be required to supply.

CO2-COP – [Hidden]

This sheet contains all of the efficiencies used as input for the CO2 system. These have been determined in DNA and are simply used as a reference sheet for the rest for the workbook. DNA files can be found in the digital folder “DNA files”.

CO2-FinalData

This sheet contains all of the calculations done to determine the performance of the CO2 system. It is quite extensive, so to increase the overview the sheet is divided into a row of sections, each outlined with a border to indicate separate calculations.

System balance due to synergy effect

Initially the demand for each energy service is converted into an amount of refrigerant that is needed, based on the cycle calculations from DNA. These are then added together to form the hourly demand for either liquid or vapor, that needs to be supplied to the system from a central location to keep it balanced.

Electricity demand

The next section calculates the electricity demand for each energy service for every hour, based on the efficiency values calculated with DNA. These are afterwards added together to form the total electricity consumption needed to satisfy all thermal demands, and finally added with the previously determined non-thermal electricity demand, to determine the total electricity demand that must be supplied.

Electricity supply

In the following section the priority of each production method is central to the functioning of the system. Several of the conditions might be true for some hours of the year, but in excel the first one to be true will break the chain, thereby skipping all other situations that might also be true. This means that the order in which the conditions are presented plays a crucial role in understanding the system.

To determine the thermal electricity production needed, it is first determined whether the system balance demands vapor or liquid production, in case liquid is needed then the electricity production is determined by the following equation, since the only implemented source of liquid production is sea based.

𝑃�� = 𝑃��+𝑃�� +𝑄��

𝐶𝑂𝑃��


If vapor production is needed to balance the system, the system becomes more advanced. Initially it is investigated whether electricity production from non-thermal sources are sufficient to meet the total electricity demand, which can for example happen in situations where large amounts of wind production have been implemented. In that case it is determined if the non-thermal production is also adequate to supply the needed electricity for the thermal production needs, meaning the heat pumps producing heating and cooling in addition to the sea-based system balancing if required, or alternatively if there is adequate stored energy to supply the deficit.

If all of those conditions are met, the CHP plants is set to deliver no power, forcing the heat production to be handled by either storage or secondary balancing measures, which in the simulated CO2 system means sea based production.

If the electricity production from non-thermal sources is inadequate then electricity production from CHP plants are needed, and it is determined whether the full vapor production resulting from the needed electricity production in combination heat production from renewable sources, i.e. solar heat or geothermal, is adequate to meet vapor production demands, in which case the CHP will simply produce the needed electricity for both thermal production and non-thermal uses. The specific distribution of heat production is distributed at a later time.

𝑄�� < 𝑄�� + 𝑄�� ⇒ 𝑃�� = 𝑃�� + 𝑃��

It should be noticed that the term QCHP-MaxVapor is utilized. This indicates the maximum amount of heat production possible at any given electrical output from the CHP plant, and is used because QCHP is freely scalable between no heat produced and full production according to rPower-to-heat = 0.8278, determined in the ThermalData sheet, dependent on the needs of the system. This variability is based on the assumption that since the plant is running in full condense mode at all times, the cooling distribution between CO2 vapor production and the sea has no effect on the efficiency of the plant.

If the maximum possible vapor production from the electricity production and additional heat from renewable sources is inadequate, then sea based balancing measures are needed and the electricity consumption for this production must be included in the electricity production. The amount of power needed can then be determined based on the amount of balancing needed from sea based production.

𝑄�� = 𝑄�� + 𝑄�� + 𝑄��

This can be rewritten into power terms, leaving PCHP as the only unknown variable.

𝑄�� =(1 −Φ��) · 𝑃��

𝑟��+ 𝑄�� + (𝑃�� − 𝑃�� − 𝑃��) · 𝐶𝑂𝑃��

By isolating PCHP the following equation is obtained, which is used to calculate the needed power production when the need for sea based balancing production has been established.

𝑃�� =(𝑄�� − 𝑄�� + (𝑃�� + 𝑃��) · 𝐶𝑂𝑃��) · 𝑟��

1 −Φ�� + 𝐶𝑂𝑃�� · 𝑟��


This process contains all the possible situations that the system must handle, and by completing it for every hour throughout the year, the appropriate power production is determined without taking savings from storage into account.

Calculating system heat balance

Having determined the appropriate electricity production, the next two sections calculate first the maximum possible vapor production, followed by the potential system balance if all vapor production were utilized. These sections are used extensively when determining how the system balances as well as when calculating how to utilize storage and sea based production.

Storage

This next section implements storage if any is implemented in the input sheet. Until now the system has been simulated without the use of storage, which means that the amount of electricity determined might change if storage for example supplies the heat needed instead of using sea based production. To take this into account the numbers will be corrected after storage has been implemented.

There are two ways of implementing storage, which will be explained in the following section. Both of these can be implemented at the same time, in which case the buffer system will take priority and attempt to balance the system. Only if the buffer system cannot deliver the required amount, the hot water storage will attempt to cover remaining demand. If both storages are empty, the sea based production will be utilized as a last resort to balance the system. In a similar way the hot water storage will not be filled unless the buffer system has reached its desired level set point.

Vapor / Liquid buffer

The system is imagined constructed by simply adding two large tanks to each of the supply lines and then using them to either supply or obtain the needed amount of CO2. The reason why the two are connected is to insure that the overall mass balance of the system is kept constant, by always adding or subtracting the same amount from each tank, meaning that if vapor is subtracted from one tank, liquid will be stored in the other tank.

Because the two tanks must either deliver or obtain mass, the desired level is initially set to 50% in each to ensure optimal balancing possibilities in each direction.

If this storage is turned on, it will first determine if there is any need for balancing in the system. If that is the case, it will supply as much as possible of the needed balancing, dependent on the amount stored liquid and vapor and the demand.

If no need for balancing is present, the system will check if the storage level is equal to the desired storage level set point, in which case no change will occur. If the storage level differs from the storage level set point, the system will determine the possibility for obtaining the needed mass of either liquid or vapor, without forcing sea based production to take effect. This means that only the amount of vapor production from CHP and renewable production can be varied to obtain the needed mass flow for the storage level to be equalized. By increasing the vapor production above system requirements it becomes possible to refill


the vapor tank or alternatively by decreasing vapor production, liquid from the network is allowed to refill the liquid tank.

The last column in the section contains the electricity saved by using the buffer, which will later be subtracted from the projected power production.

Storage of CHP plant cooling water

Another, more simple way, to introduce storage is by using large water tanks just like today. These would then be heated when excess production is available and then used for direct vapor production when the need arises. This is a very simple system, but it also has some disadvantages over the direct CO2 storage. Firstly, it is only possible to store heat, meaning that the storage cannot be used to balance the system if liquid production is needed. The storage could be imagined to contain cold water or ice, however then cooling would be needed, which would increase electricity consumption negating the effects of the storage.

Secondly, the temperature of the CHP plant cooling water during condensing operation is only approximately 20⁰C, leading to a very low temperature difference between the stored water and the CO2, thereby decreasing the amount of energy stored per mass unit in the storage.

Once again the last column in the section contains the electricity saved by using the storage, which will later be subtracted from the projected power production.

Sea based production

In some situations, the system is unable to balance the liquid and vapor lines using only the vapor production and storage. In that case, the sea is used as either a heat source or a heat sink to supply the remaining demand. This is counted as the last resort because it is the only balancing method that uses electricity to meet demand.

The procedure is simply to add all the previous contributions and then balance the remaining demand if there is any. When the needed energy production is determined, the resulting electricity consumption is calculated by dividing with the COP of the production cycle at the specific sea temperature in that hour of the year, according to the SeaTemperature and CO2-COP sheets.

Actual electricity consumption

The actual energy consumption can now be determined by subtracting the electricity saved by using storage from the amount determined to be needed without storage.

𝑃�� = 𝑃�� − 𝑃�� + 𝑃��

Coal consumption

Next the coal consumption is calculated based on the determined power production from the CHP plant. This is done simply by dividing the electricity consumption with the efficiency of the CHP plant in condensing mode, which is 42 % obtained from the ThermaData sheet, to determine the primary energy


input needed. This is then divided with the heating value of coal from the input sheet to obtain the amount of coal needed to supply the system.

Fuel costs

Finally the fuel costs are determined by multiplying the hourly amount of coal with the monthly coal price obtained from [24] and found in Excel file “Spot market Coal Prices”, to determine the price of running the system.

CO2-Plots

This sheet contains a plot of the electricity demand and CO2 mass balance for every hour throughput the year.

H2O-COP – [Hidden]

This sheet contains the COP values determined for both the refrigeration and comfort cooling processes, see Appendix 3 and 6, in the H2O system and is used as a reference sheet for the rest of the workbook.

H2O-FinalData

This sheet contains all of the calculations done to determine the performance of the H2O system. Once again it is quite extensive, so to increase the overview the sheet is divided into a row of sections, each outlined with a border to indicate separate calculations.

Thermal demand

Initially the thermal demands of the system are determined by converting the consumption values from the FinalData sheet into the production values that the system must produce to supply this consumption. For the heating this is done by adding the amount of energy that is assumed lost during transportation in the district heating pipes. For the comfort cooling and refrigeration it is done by dividing with the COP for each hour, based on the outside temperatures from the CopenhagenRefYear sheet, thereby changing the thermal energy demand into an electricity demand.

After this the thermal contribution from solar and geothermal heat is subtracted to determine the production that must be fulfilled by the thermal energy system.

These values are then added together to determine the total district heating and electricity needed to supply all the thermal demands.

Electricity production

To determine the amount of thermal electricity production needed, it is first determined whether the electricity production from non-thermal sources is sufficient to meet the total electricity demand. In that case it is determined whether heat pumps are implemented and if the non-thermal production is also adequate to supply the needed electricity for those in addition to the refrigeration and comfort cooling needs.


In that case the CHP plants is set to deliver no power and thereby no heat, forcing the heat production to be handled by either storage or secondary balancing measures, meaning either heat pumps or boilers dependent on the inputs

If the non-thermal electricity production cannot meet demand, then the program checks if there are heat pumps implemented, meaning that the electricity demand would be dependent on the heat demands. If that is not the case, then the electricity production from CHP is simply calculated by adding the electricity needed for refrigeration and comfort cooling with the demands from non-thermal uses.

𝑃�� = 𝑃�� + 𝑃�� + 𝑃��

If heat pumps are implemented, then the calculation becomes more complex because of the internal relationship between power and heating production, where the electricity consumption of the heat pumps leads to increased CHP production being necessary, which in turn leads to decreased demands from the heat pumps which leads to decreased production needs from the CHP plant. To avoid this circular reference, the following approach is utilized.

𝑄�� = 𝑄�� + 𝑄�� + 𝑄�� + 𝑄�� + 𝑄��

In the electricity calculations QBoilers can be neglected because they do not consume electricity, thus:

𝑄�� = 𝑄�� + 𝑄�� + 𝑄�� + 𝑄��

However QCHP and QHP can be expressed as

𝑄�� =(1 −Φ��) · 𝑃��𝑟��

Where rPower-to-heat = 0.6515, which is the lowest possible value since it is the highest possible heat output from the CHP plant that is relevant at this point.

𝑄�� =(𝑃�� − 𝑃�� − 𝑃��) · 𝐶𝑂𝑃��

Φ��

Resulting in the equation:

𝑄�� − 𝑄�� − 𝑄�� =(1 −Φ��) · 𝑃��𝑟��

+(𝑃�� − 𝑃�� − 𝑃��) · 𝐶𝑂𝑃��

Φ��

Which can be rewritten into:

𝑃�� =�(𝑃�� + 𝑃��) · 𝐶𝑂𝑃�� + �𝑄�� − 𝑄�� − 𝑄�� · Φ�� · 𝑟��

Φ�� − Φ�� · Φ�� + 𝐶𝑂𝑃�� · 𝑟��

Which is the equation used to determine the hourly electricity production from CHP plants if heat pumps are implemented and electricity from non-thermal sources are insufficient to supply the system.


Storage

In the storage section the program determines whether the heat demand can be satisfied with renewable sources and CHP production based on the electricity production determined. This is done within the constrains described in report section 10.1.1, meaning that the relationship between power production and heat production is variable above rPower-to-heat = 0.6515 since it is possible to produce only power, but not only heat.

If the heat demand cannot be satisfied, the deficit will be subtracted from the storage until it is empty.

If the heat demand can be satisfied without using storage, meaning that 𝑄�� < 𝑄�� + 𝑄�� then the program determines whether or not it is possible to fill additional heat into the storage using the following correlation

𝑄�� = 𝑄�� + 𝑄�� − 𝑄��

If the storage is full and there is still additional heat available, then the system will decrease the heat output from the CHP plant to increase the electrical efficiency of the cycle instead using the equation

𝜂�� =𝑃��

𝑃�� − 𝛼�� ∙ 𝑄��∙ 𝜂��

Where 𝛼�� is the negative gradient of the electrical efficiency line.

Heat pumps and boilers

If all other production measures and storage have proven unable to meet demand, then heat pumps or boilers are responsible for covering the remaining demand. The ratio between heat pumps and boilers are chosen by an input in the input sheet, and is a percentage of the total missing production that heat pumps is to produce.

Final primary energy consumption values

The systems overall consumption of primary energy can now be determined, simply by dividing the electricity consumption with the electrical efficiency and adding the boiler production divided with the boiler efficiency.

Based on the primary energy input, the coal amount is determined by dividing the total primary energy input with the energy content of coal.

Fuel costs

Finally the fuel costs are determined by multiplying the hourly amount of coal with the monthly coal price obtained from [24] and found in Excel file “Spot marked coal prices”, to determine the price of running the system.

Sce-NonThermalElec – [Hidden]


This sheet is not a part of the actual program, but merely contains some of the background work for the scenario comparing the systems when no thermal electricity production is available.


Appendix References

[1] F-Chart Software, "EES - Engineering Equation Solver," 2010.

[2] Brian Elmegaard, "Simulation of boiler dynamics - Development, Evaluation and Application of a General Energy System Simulation Tool," 1999.

[3] Wikipedia. (2011, Assessed 12.April) http://en.wikipedia.org/wiki/Carnot_cycle.

[4] Wikipedia. (2011, Assessed 13. April) http://en.wikipedia.org/wiki/Coefficient_of_performance.

[5] A.B. Eriksen, S. Grundtoft, and A.B., Lauritsen, Termodynamik, teoretisk grundlag, praktisk anvendelse.: Nyt Teknisk Forlag; ISBN 10: 87-571-2221-0, 2000.

[6] E. Granryd, I. Ekroth, Å. Melinder, B. Palm, and P. Rohlin, Refrigerating Engineering.: Department of Energy Technology, Division of Applied Thermodynamics and refrigeration, Royal Institute of Technology, KTH, Stockholm, 2005.

[7] Copenhagen Energy Ltd. (2011) http://www.ke.dk/portal/page/portal/Grafik/pdf/Fjernkoeling_engelsk_.pdf.

[8] Jan Lassen TT Coil A/S, Personal Correspondance, 2011, Regarding use of common refrigerant in comfort cooling cycles.

[9] De Europæiske Fællesskabers Tidende, "Europa-Parlamentets og rådets forordning (EF) Nr. 2037/2000 om stoffer, der nedbryder ozonlaget," 2000.

[10] AIA Calc. (2011) http://www.tt-coil.dk/Default.aspx?PagId=96.

[11] Bitzer Software. (2011) http://bitzer.de/eng/productservice/software/1.

[12] T. Schmidt Ommen, Personal Correspondance, 2011, Temperature levels in supermarket cooling systems.

[13] T.S. Ommen and B. Elmegaard, "Thermoeconomic model of a commercial transcritical booster refrigeration system," in ECOS, 2011.

[14] DTU-MEK. http://www.et.web.mek.dtu.dk/coolpack/download.html.

[15] Heat Exchange Institute, "Tech Sheet #113," 2005.

[16] K. Capion, Personal Correspondance, 2011, Return water temperatures in DH pipelines.


[17] M.J. Skovrup, Regarding CO2 compressor coefficients, 2011, Personal Correspondance.

[18] G. Haiqing, M. Yitai, and L. Minxia, "Some design features of CO2 swing piston expander," Applied Thermal Engineering, vol. 26, pp. 237-243, 2006.

[19] Bitzer, "KT-660 - 2, Application of Propane (R290) with semi-hermetic Reciprocating Compressors," 1997.

[20] J.T. Larsen, Dansk Supermarked, Regarding supermarket refrigeration system performance, 2011, Personal Correspondance.

[21] SBi, "Varmt brugsvand - Måling af forbrug og varmetab i cirkulationsledninger," 2009.

[22] L. Gissel, DAB Energigruppe, Regarding the residential blocks "Værebro" and "Høje Søborg II", 2011, Personal Correspondance.

[23] Furbo, S. DTU Civil Engineering, Personal Correspondance, 2010, Weather data from reference year.

[24] Energistyrelsen C. (2011, July) http://www.ens.dk/da-DK/Info/TalOgKort/Statistik_og_noegletal/Energipriser_og_afgifter/Kulpriser/Sider/Forside.aspx.

[25] Department of Mechanical Engeneering at DTU. (2011) http://www.et.web.mek.dtu.dk/coolpack/uk/download.html.

[26] Robert X. Perez. (2011, August) Pumps and Systems, The Resource For Pump Users Wrldwide. [Online]. http://www.pump-zone.com/compressors/compressors/why-compression-ratio-matters.html

http://www.pump-zone.com/compressors/compressors/why-compression-ratio-matters.html

DTU Mechanical Engineering

Section of Thermal Energy Systems

Technical University of Denmark

Nils Koppels Allé, Bld. 403

DK- 2800 Kgs. Lyngby

Denmark

Phone (+45) 45 25 41 31

Fax (+45) 45 88 43 25

www.mek.dtu.dk

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