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The final colloquium presentation of my graduation. The graduation theme is “Electrical and thermal energy balance analysis for an off-grid campground site”. The graduation research is performed at the Eindhoven University of Technology (TU/e) in the research group of prof.dr.ir Jan Hensen.
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Electrical and thermal energy balance analysis for an off-grid campground siteDecember 20th, 2011
Graduation supervisorsprof.dr.ir. J.L.M. Hensendr.dipl.-ing M. TrckaB. Lee MSc
External member graduation committeedr.ing. A.J.M. Pemen
ing. Jeroen van Hellenberg Hubar
13-04-2023
Outline
• Introduction
• Research Question
• Methodology
• Case study
• Results from case study
• Conclusion
• Future work
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Introduction
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Energy
Source: www.tue.nl
“Amount of work that can be performed by a force”
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Introduction
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Photosynthesis Evolution
One of the most important physical quantities
Source: www.sience.howstuffworks.com Source: www.viewshound.com
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Introduction
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Horse manure crisis
Used in abundance and misguided
• 19th century dependent on horses
• Horse power resulted in negative
side effects:• Manure (health)• Noise pollution• Accidents
• 1898 first international urban- planning conference in New York was abandoned after 3 days.
?Automobile
Source: www.melbourneubanist.wordpress.com Source: www.wikipedia.com
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Introduction
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Still creating new problems
Energy generation Green house gas emissions
Source: www.tue.nl Source: www.pearls-necklaces.com
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Introduction
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IPCC climate change report 2007• CO2 emission is the main cause of temperature
rise • 86% of CO2 emission is addressed to energy
Building sector• Accounts for 30% of the global CO2 emission.
IEA ETP 2010 report• Baseline scenario assume energy use in 2050 is roughly doubled compared to 2007.
IPCC: Intergovernmental Panel on Climate ChangeIEA ETP: International Energy Agency, Energy Technology Perspective
Emissions in the building sector nearly double.
Source: www.biomonicfuel.comSource: www.corporatienl.nl
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Introduction
PAGE 8/38
Current energy situation
Buildings are mainly connected to the grid• Electricity• Gas
Source of energy neither a choice nor concern• Limited possibility to reduce the carbon
dioxide emission produced by energy generation
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Introduction
PAGE 9/38PAGE 913-04-2023
Remote area
• Buildings could be completely off-grid• Energy could be provided with an off-
grid energy source.
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Introduction
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IEA ETP 2010 reportBLUE maps scenario• 50% reduction of CO2 emission in 2050• 2/3 reduction of CO2 emission in the building sector
Introducing:• Energy efficient technologies • Low carbon technologies
Solar cells / panels, heat pumps, Combined heat and Power (CHP)
Source: www.corporatienl.nl
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Introduction
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Research Question
“How to develop a design concept which ensures the comfort of the occupants, and has an optimized energy system with 100% renewable micro-generation technologies which has to satisfy the electrical and thermal energy demand, for an off-grid community?”
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Methodology
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Case study
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Off-grid community
• Island of Texel in the Netherlands• Off-grid community Off-grid campground• Lot of campgrounds located on the island of Texel• Weather station Den Helder airport
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Case study
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Source: Auto Camper Service International (ASCI) guide
Central Bureau of Statistics of the Netherlands (CBS)
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Case study
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Local comfort norms
Domestic Hot Water (DHW)
Sources:
Knowledge Institute for the installation technology sector (ISSO)
Association of water companies in the Netherlands (VEWIN)
IEA Solar Heating & Cooling program (IEA-SHC Task 26)
• Only water of 60oC is considered• An unlimited supply of cold
water (10oC) is assumed
Space heating
• Space cooling is left out of the research.
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Case study
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Local comfort norms
Electricity
Source: Agentschap NL, Numbers & figures, 2007
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Case study
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Energy demand
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Case study
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Community buildings
• Buildings’ geometry is designed in Google SketchUp• Buildings’ specifications are defined in TRNSYS
• According to the numbers of the reference buildings of AgentschapNL
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Case study
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Energy Technology
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Case study
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Energy TechnologyGenerate energy at each opportunityGenerate energy on demandBalance energy deficit and/or surplus
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Case study
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Simulation
Simulation model in TRNSYS• Flexibility and capability of modeling energy technologies• Entire energy system can be broken down into individual components• Flow of information from one component to the other
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Case study
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Case study
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Optimization
Optimization model in modeFRONTIER• The aim of optimization is to solve problems in a systematic way by producing a set of
solutions based on pre defined objectives that are functions of design variables
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Case study
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Optimization
• Energy• CO2
• Investment cost
• Minimize the life time carbon dioxide emissions• Reason: IPCC 2007 report states GHG, in specific CO2, are main causes of the temperature change on earth
• Minimize the investment cost of the energy technologies• Reason: Real life decisions are made upon investment costs
• The main issue of energy is, the way the energy is generated. The community is allowed to use energy, but with low CO2 emissions.• Research focus is not on reducing the energy
demand but on balancing the energy demand and generation.
Objective functions
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Case study
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Optimization
Objective function: Life cycle carbon dioxide emission
Source: IEA / OECD, Benign energy? The environmental implications of renewables. 1998
IEA, full cycle atmospheric emission and global warming impact from UK electricity generation, 1995
D. Lopez, MOO minimizing cost and life cycle emissions of pv-wind-diesel systems with battery storage, Applied energy, 2011
D. Saner et. al, Is it only CO2 that matters? A life cycle perspective on shallow geothermal systems, ren. and sust. Energy, 2010
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Case study
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Optimization
Objective functions: Investment cost
Source: Agentschap NL, Numbers & figures, 2007
A. Akhil et al, Cost analysis of energy storage systems for electric utility applications, 1997
C. Parker, Lead-acid battery energy storage systems for electricity supply network, journal of power sources, 2001
www.aosmithinternational.com, 2011
www.krcon.nl/kostencentrum/diensten, 2011
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Case study
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Optimization
Objective functions
Decision Variables
• Variable input in model• Installed capacity of the
energy technologies
Design Constraints
• To approach a real situation• Defined by norms and the
simulation software
Optimization Algorithm
• Multi Objective • DoE; provide the algorithm
with an initial population of designs
• DoE: ULH, Uniform distribution of installed capacity with same probability.
• GA: successfully used in building performance
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Case study
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Post processing
Post processing provides a way to process the obtained dataset
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Results derived from case study
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Post processing
Design constraints; 2000 generations 1345 feasible configurations
32% 70% 30%
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Results derived from case study
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70% 30%
Configuration
• Energy system configuration
Energy system shows a trend!
Topmost 50%Min. CO2Topmost 50%Min. costTopmost 25%Min. CO2Topmost 10%Min. CO2Topmost 25%Min. costTopmost 10%Min. costTopmost 25%Both objectives!
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Carbon dioxide emission
• CO2 emission battery• Lead acid battery• Life cycle emission
• Collecting• Producing• Decommissioning
• CO2 emission CHP
Results derived from case study
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Investment cost
• Investment cost CHP (electrical)
• Cost per installed capacity• CHP generated electrical & thermal energy• High amount of annual production hours
CHP important technology
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Results derived from case study
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32% 70% 30%
Pareto Front
• Optimization Space • Trade-off between objectives• 5 best possible
solutions
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Results derived from case study
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32% 70% 30%
Decision making
Stakeholder perspective• International Energy Agency (IEA)
• Goal: Performance based solutions for energy efficient and environment friendly buildings & communities, that support sustainability and produce carbon-free energy according demand
Investment cost• Both configurations in the same order of magnitude
Stakeholders strategic plan• Highest share and visibility of sustainable energy generation
technologies is more favorable
5 1
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Conclusion
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32% 70% 30%• Methodology successfully applied on the campground.• A distinct trend was spotted in the energy system configurations
• CHP is an important technology • Low installed capacity cost• Low life cycle carbon dioxide emission• Simultaneous energy production• High annual production hoursONLY VALID FOR THIS MODEL CONFIGURATION
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Conclusion
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In ideal decision making between technologies, one technology is independently evaluated to others.
In the case study, energy technologies became interconnected, controlled and dependent on the specifications from each other.
For example: The control strategies for energy technologies The control of the water buffer temperature The in/out flow and temperature of thermal circuit.
Not a full energy system spectrum optimization with independent energy technologies could be performed.
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Conclusion
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Therefore the results are only valid for this case study• For the chosen energy technologies• In this specific configuration• With the specific control strategies
Nevertheless the design concept can be used to come to an optimized energy system.
64 possibilities!4 possibilities!
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Conclusion
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32% 70% 30%
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Future work
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1. Add the two analyses• Both of the analyses support the decision making by providing additional
information on the parameters chosen• Sensitivity Analysis: Identify the most influential decision variables• Uncertainty analysis: Explore the impact on outcome due to uncertainties in
the input
2. Research on other simulation tools than TRNSYS• Request a detailed input, use more abstract tool for energy systems
3. Perform a new case study to demonstrate the design concept• Create a variable occupancy profile • Include thermal & electrical losses• Simulate the electrical energy in a load flow model• Update the research on the prize level of sustainable energy technologies
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Future work
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Keep all the possible (energy technology) configurations open
No choices, even unaware, are made which bound the optimization space.
4 possibilities!64 possibilities!
Electrical and thermal energy balance analysis for an off-grid campground siteDecember 20th, 2011
Graduation supervisorsprof.dr.ir. J.L.M. Hensendr.dipl.-ing M. TrckaB. Lee MSc
External member graduation committeedr.ing. A.J.M. Pemen
ing. Jeroen van Hellenberg Hubar
