Heating and cooling energy demand and loads for building ... · PDF fileHeating and cooling energy demand and loads for building types in different countries of the EU ... The loads

Heating and cooling energy demand and loads for building types in different

countries of the EU

D2.3. of WP2 of the Entranze Project

Written by:

Paolo Zangheri, Roberto Armani, Marco Pietrobon and Lorenzo Pagliano (eERG) end-use Efficiency Research Group Politecnico di Milano Maria Fernandez Boneta (CENER) National Renewable Energy Centre Andreas Müller (EEG) Vienna University of Technology

Reviewed by:

Judit Kockat, Clemens Rohde Fraunhofer ISI

March 2014

Heating and cooling energy demand and loads for building types in different countries of the EU

2

ENTRANZE Project

Year of implementation: April 2012 – September 2014

Client: EACI

Web: http://www.entranze.eu

Project consortium:

EEG Energy Economics Group Institute of Power Systems and Energy Economics Vienna University of Technology

NCRC National Consumer Research Centre

Fraun-hofer

Fraunhofer Society for the advancement of applied research

CENER National Renewable Energy Centre

eERG end use Efficiency Research Group, Politecnico di Milano

Oeko Öko-Institut

SOFENA Sofia Energy Agency

BPIE Buildings Performance Institute Europe

Ener-data

Enerdata

SEVEn SEVEn, The Energy Efficiency Center


3

The ENTRANZE project

The objective of the ENTRANZE project is to actively support policy making by providing the required data, analysis and guidelines to achieve a fast and strong penetration of nZEB and RES-H/C within the existing national building stocks. The project intends to connect building experts from European research and academia to national decision makers and key stakeholders with a view to build ambitious, but reality proof, policies and roadmaps. The core part of the project is the dialogue with policy makers and experts and will focus on nine countries, covering >60% of the EU-27 building stock. Data, sce-narios and recommendations will also be provided for EU-27 (+ Croatia and Serbia). This report provides an overview of the energy needs for heating, cooling and DHW1 for sev-eral building types, located in different European climatic contexts. It includes main build-ings characteristics of the base cases defined within WP22 and WP3 and first simulation results carried out during WP2.

Acknowledgement:

The authors and the whole project consortium gratefully acknowledge the financial and intellectual support of this work provided by the Intelligent Energy for Europe – Pro-gramme.

Legal Notice:

The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the European Union. Neither the EACI nor the European Commission is responsible for any use that may be made of the information contained therein.

All rights reserved; no part of this publication may be translated, reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. The quotation of those designations in whatever way does not imply the conclusion that the use of those designations is legal without the consent of the owner of the trademark.

1 DHW = domestic hot water

2 WP = work package


4

Content

The ENTRANZE project .............................................................................................................. 3

Content ......................................................................................................................................... 4

Executive Summary .................................................................................................................... 6

1. Methodology ........................................................................................................................ 7

1.1 Calculation tools .......................................................................................................... 7

1.1.1 EnergyPlus ..................................................................................................... 7

1.1.2 EN 13790 (simple hourly three-nodes model) ................................................ 8

1.1.3 INVERT/EE-Lab – Thermal Module ............................................................. 11

1.2 Reference building types ........................................................................................... 13

1.2.1 Single house ................................................................................................. 14

1.2.2 Apartment block ............................................................................................ 16

1.2.3 Office ............................................................................................................ 18

1.2.4 School ........................................................................................................... 20

1.3 Reference climatic contexts ...................................................................................... 22

2. Calculation of energy needs using the EnergyPlus tool ............................................... 26

2.1 Single house .............................................................................................................. 27

2.1.1 Seville (ES) ................................................................................................... 27

2.1.2 Madrid (ES) ................................................................................................... 28

2.1.3 Rome (IT) ...................................................................................................... 29

2.1.4 Milan (IT) ....................................................................................................... 30

2.1.5 Bucharest (RO) ............................................................................................. 31

2.1.6 Vienna (AT) ................................................................................................... 32

2.1.7 Paris (FR) ..................................................................................................... 33

2.1.8 Prague (CZ) .................................................................................................. 34

2.1.9 Berlin (DE) .................................................................................................... 35

2.1.10 Helsinki (FI) ................................................................................................... 36

2.2 Apartment block ......................................................................................................... 37

2.2.1 Seville (ES) ................................................................................................... 37

2.2.2 Madrid (ES) ................................................................................................... 38

2.2.3 Rome (IT) ...................................................................................................... 39

2.2.4 Milan (IT) ....................................................................................................... 40

2.2.5 Bucharest (RO) ............................................................................................. 41

2.2.6 Vienna (AT) ................................................................................................... 42

2.2.7 Paris (FR) ..................................................................................................... 43

2.2.8 Prague (CZ) .................................................................................................. 44

2.2.9 Berlin (DE) .................................................................................................... 45


5

2.2.10 Helsinki (FI) ................................................................................................... 46

2.3 Office ......................................................................................................................... 47

2.3.1 Seville (ES) ................................................................................................... 47

2.3.2 Madrid (ES) ................................................................................................... 48

2.3.3 Rome (IT) ...................................................................................................... 49

2.3.4 Milan (IT) ....................................................................................................... 50

2.3.5 Bucharest (RO) ............................................................................................. 51

2.3.6 Vienna (AT) ................................................................................................... 52

2.3.7 Paris (FR) ..................................................................................................... 53

2.3.8 Prague (CZ) .................................................................................................. 54

2.3.9 Berlin (DE) .................................................................................................... 55

2.3.10 Helsinki (FI) ................................................................................................... 56

2.4 School ........................................................................................................................ 57

2.4.1 Seville (ES) ................................................................................................... 57

2.4.2 Madrid (ES) ................................................................................................... 58

2.4.3 Rome (IT) ...................................................................................................... 59

2.4.4 Milan (IT) ....................................................................................................... 60

2.4.5 Bucharest (RO) ............................................................................................. 61

2.4.6 Vienna (AT) ................................................................................................... 62

2.4.7 Paris (FR) ..................................................................................................... 63

2.4.8 Prague (CZ) .................................................................................................. 64

2.4.9 Berlin (DE) .................................................................................................... 65

2.4.10 Helsinki (FI) ................................................................................................... 66

2.5 Summary ................................................................................................................... 67

3. Comparison of the EnergyPlus results with the simply hourly EN13790 and

INVERT/EE-Lab approach ................................................................................................. 71

3.1 Single house .............................................................................................................. 73

3.2 Apartment block ......................................................................................................... 76

3.3 Office ......................................................................................................................... 79

3.4 School ........................................................................................................................ 81

3.5 Conclusion ................................................................................................................. 84

References ................................................................................................................................. 86


6

Executive Summary

This ENTRANZE working paper presents the main results of the heating and cooling loads’ analysis and the energy demand for representative building types. The main con-tributors in this project are the end-use Efficiency Research Group of Politecnico di Mi-lano (IT), the National Renewable Energy Centre (ES) and the Energy Economics Group from the Vienna University of Technology.

Based on the definition of building types3 and in partial overlap with the cost-optimality analysis4, the results obtained within this Task (2.2) for several reference cases are used to calibrate the thermal calculation module in the model Invert/EE-Lab. With this model the thermal loads and energy needs (for heating, cooling and DHW) of all building types in investigated EU countries can be derived, which is the basis for the development of scenarios and policy analyses in work package 4.

The calculation activities presented in this paper are carried out using a dynamic tool (EnergyPlus) adopting a common methodology of simulation. There are 4 different base cases (single family house, apartment block, office and school) in 10 relevant European cities with high relevance and characterised by different climatic conditions. The selected base cases referred to are national building stocks from 1960 to 1970. An online data tool prepared by the whole ENTRANZE consortium reflecting detailed thermal charac-teristics of building types.

ENTRANZE is a European project that in principle covers all EU-27 countries. The geo-graphical scope of the project is divided into target countries, focus countries and other countries. In terms of the scope, this deliverable (D2.3) focuses on the nine following countries: Austria, Bulgaria, Czech Republic, Finland, France, Germany, Italy, Romania and Spain.

The report is structured as follows: Chapter 1 discusses the methodology used for esti-mating the thermal energy needs within the ENTRANZE Project. Furthermore, it defined the reference buildings and key climatic conditions. Chapter 2 shows the results obtained by the dynamic simulation. In Chapter 3, the results using a simplified tool (spreadsheet) based on the Standard EN ISO 13790 and the results from the dynamic simulation are compared with the outcomes of the thermal module in Invert/EE-Lab. Finally, the differ-ences of the described approaches are concluded and discussed.

3 For results on the building stock analysis conducted in work package 2, please refer to the

online data tool http://www.entranze.enerdata.eu/ country reports or the country reports http://www.entranze.eu/publications/building-sector-and-its-energy-demand.

4 For results on the analysis of global cost performed in work package 3, please refer to the fol-lowing report: http://www.entranze.eu/publications/cost-data.


7

1. Methodology

In order to achieve a higher quality of outputs, the estimation of energy need is carried out in close connection with the previous data collection phase (Task 2.1-3) as well as with the tools applied in WP3 and WP4.

Fig. 1: Entranze activities involved in the calculation of the energy needs.

In the following paragraphs we discuss the tools used, as well as the preliminary results obtained, about the characterisation of building prototypes and the selection of key cli-matic conditions within the Entranze Target area.

1.1 Calculation tools

1.1.1 EnergyPlus

EnergyPlus is one of the most used and reliable program for energy analysis and thermal load simulation. It is based on a description of the building’s physical make-up, its asso-ciated mechanical systems, etc. EnergyPlus is able to calculate the heating and cooling loads dynamically. The loads are necessary to maintain thermal control setpoints and conditions. Moreover, the tool covers secondary HVAC system, coil loads, the energy

Task 2.1-3

ESES CZCZ FRFR FIFI AUAU BUBU ITIT DEDE

data collection

WP4

Task 2.2

selection

WP3

simulation-calculation EN13790

comparison

INVERT calibration

calculationINVERT


8

consumption of primary plant equipment and other simulation details. These data are necessary to verify that the simulation is performing as the actual building would. Many of the simulation characteristics have been inherited from the legacy programs of BLAST and DOE–2.

Fig. 2: EnergyPlus Program Schematic.

The principal program modules involved in the calculation of the energy need for heating and cooling are the Surface Heat Balance and Air Heat Balance managers (with their sub-modules).

For more information see “EnergyPlus Engineering Reference”5.

1.1.2 EN 13790 (simple hourly three-nodes model)

This method takes in account the calculation for: thermal exchange for transmission and ventilation of the building zone when it is warmed or cooled at a constant set point tem-perature, the contribution of internal and solar thermal gain and, as a consequence, the annual energy need for heating and cooling of thermal zones.

The used procedure calculates only the sensible component of heating and cooling (whereas the latent component is not considered). The building is described as a single zone with boundaries are determined by surfaces in contact with external air, ground or non-conditioned zones.

5 http://apps1.eere.energy.gov/buildings/energyplus/pdfs/engineeringreference.pdf


9

The considered geometrical input data has been:

- the total net floor surface and the net volume of the inner air of the thermal zone (building);

- the areas of building surfaces (both opaque and transparent) that delimitates the thermal zone, subdivided on the base of exposition. Only surfaces facing on ex-ternal air, ground or non-conditioned zones were entered;

- the percentage of transparent surfaces on total areas (both opaque and trans-parent) for each exposition;

- the length of thermal bridges. The required physical proprieties have been:

- the average thermal transmittance and absorption coefficient, for opaque sur-faces;

- the average thermal transmittance and the their solar factor, for windows; - the linear thermal transmittance, for thermal bridges.

The internal thermal capacity of the zone can be determined according to EN ISO 13786 standard, or by adopting default values indicated in EN 13790 standard on the base of qualitative evaluation of the mass of building components [J/K] (very light, light, medium, heavy, very heavy). With the aim to simplify the data collection (according to Invert Model requirements), the default values reported in EN 13790 standard are applied to the net floor surfaces only.

The simplified hourly dynamic method for energy need calculation allows the definition of the time schedule for monthly and hourly functioning of different building parameters. In the former case, the monthly schedule data which can be entered are: heating and cooling periods, solar shading activation and free cooling strategies by means of night ventilation (between 11 p.m. to 7 a.m. for all days of the cooling period). In the latter case, the inputted hourly schedule data are: internal gain [W/m2], air exchanges [h-1] for both heating and cooling periods, the extra air flow due to night ventilation [h-1] only in the cooling period as well as the set point temperatures for both heating and cooling. However, it is not possible to insert weekly schedule considering a different building use during week end.

The required climate data have been:

- average monthly temperature [°C]; - average of daily max temperature for each month [°C]; - monthly mean daily solar radiation on horizontal surfaces [kJ/(m2day)]; - latitude;

The sensible thermal energy need for heating and cooling are calculated starting from:

- thermal exchange for transmission between conditioned zone and outdoor, that is depending of the temperature difference between these zones;


10

- thermal exchange for ventilation (natural or mechanical ventilation), that is de-pending of the difference between indoor temperature and temperature of sup-plied air;

- internal thermal gain due to people presence, lighting, appliances and due to the heating loss by heating, cooling, hot water and ventilation plants;

- solar thermal gain (from windows and opaque surfaces); - heat storage or loss by building mass.

The used method is based on the hourly R-C methods at three nodes (resistive capaci-tive equivalent method – hourly at three nodes). This model determines a distinction between indoor air temperature and mean radiant surface temperatures (for internal sur-faces facing an zone to be calculated). This approach increases the accuracy by taking into account the radiant and convective components of thermal, solar and lighting internal gain.

The energy need for heating and cooling is determined by calculating the monthly mean power for heating and cooling (HC,nd positive for heating and negative for cooling) re-

quired (through extraction or supply of air power) for each hour by corresponding node of internal air, air, to maintain a min or max determined temperature.

The set point temperature is a weighted average between air temperature and mean radiant temperature. The default weighted factor for both temperature is 0,5.

The thermal exchange for ventilation - Hve - is directly related to the node that corre-sponds to air temperature - air - and to the node which represents the supplied air tem-perature - sup. The thermal exchange for transmission is separated in the windowed portion (including doors and windows) - Htr,w -, which is considered as thermal mass=0. The remaining portion of the surfaces - Htr,op -, includes a thermal mass, which is, in turn, split in two part: Htr,em (emission) and Htr,ms (conductance). The solar and indoor thermal gain are distributed on node of air, air, on central node, s (which is a combination of air and mean radiant temperature - r,mn) and on the node representing the mass of the building zone, m. The thermal mass is defined by a single thermal capacity, Cm, localized between Htr,ms and Htr,em. A coupling conductance is defined between node of internal air and central node. The thermal flow due to inner heat sources, int, and the thermal flow due to solar thermal sources, sol, are subdivided between the three nodes.


11

Fig. 3: Scheme of the R-C methods at three nodes

1.1.3 INVERT/EE-Lab – Thermal Module

Invert/EE-Lab is a bottom-up simulation tool that evaluates the effects of different pro-motion schemes (in particular different settings of economic and regulatory incentives) on the energy carrier mix, CO2 reductions and costs for RES-H support policies. Further-more, Invert/EE-Lab is designed to simulate different scenarios (price scenarios, insula-tion scenarios, different consumer behaviours, etc.) and their respective impact on future trends of renewable as well as conventional energy sources on a national and regional level.

The core of the tool is a myopical, nested logit approach, which optimizes objectives of “agents” under imperfect information conditions and by that represents the decisions maker concerning building related decisions. Invert/EE-Lab models the stock of buildings in a highly disaggregated manner. Therefore the simulation tool reflects some character-istics of an agent based simulation.

A main output of the model Invert/EE-Lab is the annual delivered energy for each building segment. The delivered energy is derived from the monthly energy need (energy need for space heating, cooling and hot water). This document deals only with the calculation of the energy need, not with the other modules of the model Invert/EE-Lab.


12

The overall energy need of the building stock in a region or country is modelled for monthly based on the energy need in each building class (subset of buildings which share the same building geometry and envelope specifications, climate zone and usage).

The energy need of each building class is calculated by using a monthly energy balance approach, quasi-steady-method, enhanced by explicitly distinguishing between using and non-using days and in case for ventilation between average day (16 hours) and night (8 hours) outside air temperatures.

The methodology has been implemented based on the following literature, Austrian, Ger-man and EU standards:

1. Pöhn Christian: "Bauphysik. Erweiterung 1, Energieeinsparung und Wärme-schutz ; Energieausweis - Gesamtenergieeffizienz”, Vienna: Springer-Ver-lag/Wien, 2007;

2. ÖNORM B 8110-5; 3. ÖNORM H 8055; 4. DIN V 4108-6; 5. DIN V 4701-10; 6. EN ISO 13790: 2008: Quasi-steady-state method.

The monthly energy need for space heating is calculated as a balance of heat gains and heat transfers and is multiplied by the utilization factor (see equation 1). The monthly utilization factor shows that only a part of the internal and solar heat gains are utilized to decrease the energy need for heating. The utilization factor depends (mostly) on the building construction type. The annual energy need is the sum of monthly en-ergy needs.

∙ (1)

where:

is the total heat transfer [MJ];

is the monthly utilization factor; are the total heat gains [MJ].

The monthly heat transfer is the sum of the transfer by transmission and transfer by ventilation . The calculation of the month heat transfer requires the set-point temper-ature of the building, which is determined for each user profile and the monthly temper-ature of the external environment. To calculate the heat transfer by transmission, the data of the building elements, which are the area and the thermal transmittance of a building element, are taken into account. To calculate the heat transfer by ventilation , the buildings are split into buildings with ventilation system and without ventilation system. If there are no ventilation system losses by transmission losses are equal to


13

window ventilation. In another case the transfer by ventilation depends on the heat re-covery unit of a ventilation appliance.

The monthly heat gains are calculated as a sum of the monthly internal heat gains and monthly solar heat gains . Calculation of the internal heat gains require the specific heat gain, which is taken for each user profile, and net floor area of the building. Solar heat gains from solar heat sources result from solar radiation through the windows with consideration of shading reduction factors. These require establishing the glass area of a building, solar energy transmittance of glazing and the shading corrector factor.

The monthly energy need for space cooling is calculated equal to the energy for space heating, but this heat has to be extracted from a conditioned space. However, additional to the calculation of the solar heat gains the shading factor and solar heat input through opaque building elements are considered. The shading factor depends on the material type of the shading element. In order to calculate heat input through opaque building elements, correcting factor regarding the colour and angle of the relevant building com-ponents are used.

The monthly energy need for hot water is calculated by introducing specific energy need for warm water which is defined for each user profile and is given in table “user profiles”. It is calculated as shown in equation 2:

,

1

1000∙ ∙ ∙ (2)

where:

wwwb is the specific energy need for warm water;

BF is the gross floor area [m2];

are the days per month [d/M].

1.2 Reference building types

Evaluating as strategic the building renovation sector – in accordance with the premises and objectives of the Entranze Project – this analysis has been focused on the building age more representative of the existing building stock in EU: years 60’s - 70’s.

Starting from the data collected within Task 2.1 and through additional data collection templates, we characterized 4 building types (2 residential and 2 tertiary) in 8 target countries. Due to similarities of the climate between Romania and Bulgaria, the latter was not simulated in this report, although it is target country in other tasks of the project ENTRANZE.


14

1.2.1 Single house

The building which has been selected as reference for single family house, (composed by an underground level and two floors over ground level) has a conditioned surface of about 140 m2 and a S/V ratio of 0.7. The main other characteristics (fixed and variable by Country) involved on the simulation task are shown below.

North façade South façade

East façade

West façade

Fig. 4: Prospects of the single house model.


15

Tab. 1: Fixed characteristics of the single house model. All Countries

Bu

ildin

g g

eom

etry

N° of heated floor = 2

S/V ratio = 0.7 m2/m3

Orientation: S/N

Net dimensions of heated volume = 8.5 x 8.5 x 6 m

Net floor area of heated zones = 140 m2

Area of S façade = 51 m2

Area of E façade = 51 m2

Area of N façade = 51 m2

Area of W façade = 51 m2

Area of Roof = 72.25 m2

Area of Basement = 72.25 m2

Window area on S façade = 25%

Window area on E façade = 7%

Window area on N façade = 25%

Window area on W façade = 7%

Inte

rnal

g

ain

s People design level = 50 m2/people

Lighting design level = 3.5 W/m2

Appliances design level = 4 W/m2

Tab. 2: Variable characteristics of the single house model.

ES IT RO AT FR CZ DE FI

Bu

ildin

g t

ech

no

log

ies

Construction materials:

A A A A A A A B

Typical infil-tration rate:

0.77 0.77 0.77 0.77 0.77 0.77 0.77 0.77 h‐1

U value of wall =

1.46 1.21 1.45 1.25 1.54 1.32 0.93 0.48 W/m2K

U value of roof =

1.92 1.69 1.60 1.39 1.20 1.32 1.10 0.30 W/m2K

U value of basement =

1.30 1.69 1.30 1.77 1.97 1.24 1.01 0.48 W/m2K

U value of glass =

5.70 3.20 2.40 2.70 4.20 2.90 2.57 2.79 W/m2K

g value of glass =

0.89 0.80 0.75 0.75 0.80 0.75 0.75 0.75 -

Passive strategies:

In Summer: shading device + ventilation at night

A: Brick, concrete, plaster

B: Brick, insulation, concrete, plaster


16

1.2.2 Apartment block

The building which has been selected as reference for apartment block (four floors + cellar) is composed by about 12-16 flats and its conditioned area is around 1000 m2 and a S/V ratio of 0.33. The main other characteristics (fixed and variable by Country) in-volved on the simulation task are shown below.

North façade South façade

Fig. 5: Prospects of the apartment block model.


17

Tab. 3: Fixed characteristics of the apartment block model.

ES, IT, FR

RO, AT, CZ, DE, FI

Bu

ildin

g g

eom

etry

N° of heated floor = 4 S/V ratio = 0.33 m2/m3 Orientation: S/N Net dimensions of heated volume = 24.6 x 11.2 x 12.8 m Net floor area of heated zones = 990 m2 Area of S façade = 315 m2 Area of E façade = 143 m2 Area of N façade = 315 m2 Area of W façade = 143 m2 Area of Roof = 54 m2 Area of Basement = 54 m2 Window area on S façade = 15% 30% Window area on E façade = 0% 0% Window area on N façade = 15% 30% Window area on W façade = 0% 0%

Inte

rnal

g

ain

s People design level = 25 m2/people Lighting design level = 3.5 W/m2 Appliances design level = 4 W/m2

Tab. 4: Variable characteristics of the apartment block model.


Bu

ildin

g t

ech

no

log

ies


A A C B B B B B

Typical ACH rate:

0.77 0.77 0.77 0.77 0.77 0.77 0.77 0.77 h‐1

U value of wall =

1.46 1.21 1.45 1.25 2.86 0.65 1.44 0.60 W/m2K

U value of roof =

1.92 1.69 1.20 1.39 2.56 0.65 1.17 0.39 W/m2K


1.30 1.69 1.30 1.77 1.98 1.26 1.50 0.47 W/m2K

U value of glass =

5.70 3.30 2.40 2.70 3.80 2.90 2.11 2.79 W/m2K

g value of glass =

0.89 0.80 0.75 0.75 0.80 0.75 0.75 0.75 -

Passive strategies:


A: Hollow brick, air gap, concrete, plaster

B: Concrete, plaster

C: Prefabricated panel, concrete, plaster


18

1.2.3 Office

As reference of office building, a medium-size and highly-glazed office building has been selected, with 5 floors (of 3 m height each) an S/V ratio of 0,33 and a net heated area of 2400 m2. The main other characteristics (fixed and variable by Country) involved on the simulation task are shown in the following tables.

South façade

East façade

North façade

West façade

Fig. 6: Prospects of the office building model.


19

Tab. 5: Fixed characteristics of the office building model. All Countries

Bu

ildin

g g

eom

etry

N° of heated floor = 5 S/V ratio = 0.33 m2/m3 Orientation: S/N Net dimensions of heated volume = 30 x 16 x 15 m Net floor area of heated zones = 2400 m2 Area of S façade = 450 m2 Area of E façade = 240 m2 Area of N façade = 450 m2 Area of W façade = 240 m2 Area of Roof = 480 m2 Area of Basement = 480 m2 Window area on S façade = 56% Window area on E façade = 32% Window area on N façade = 50% Window area on W façade = 35%

Inte

rnal

g

ain

s People design level = 18 m2/people Lighting design level = 14 W/m2 Appliances design level = 9 W/m2

Tab. 6: Variable characteristics of the office building model.


Bu

ildin

g t

ech

no

log

ies


A A C B A C B B

Typical ACH rate:

1.15 1.15 0.92 1.60 1.15 1.15 1.15 1.45 h‐1

U value of wall =

1.37 1.17 1.34 1.16 1.06 1.07 1.42 0.46 W/m2K

U value of roof =

1.29 1.28 1.01 1.11 1.65 0.50 0.68 0.39 W/m2K


1.36 1.74 1.10 1.24 1.74 3.93 1.14 0.52 W/m2K

U value of glass =

5.70 3.20

- 5.70

2.40 2.70 5.70 4.00 2.90 3.20 W/m2K

g value of glass =

0.89 0.80

- 0.89

0.75 0.80 0.89 0.85 0.80 0.85 -

Passive strategies:

Shading device controlled in summer by occu-pant

A: Hollow brick, air gap, concrete, plaster

B: Concrete, insulation, plaster



20

1.2.4 School

As reference model of school a two-floors building has been selected. It is “U” shaped with a heated surface of 3500 m2 and its S/V ratio is 0.46. The main other characteristics (fixed and variable by Country) involved on the simulation task are shown in the following tables.

South/North façade

East façade

West façade

Fig. 7: Prospects of the school model.


21

Tab. 7: Fixed characteristics of the school model. All Countries

Bu

ildin

g g

eom

etry

N° of heated floor = 2 S/V ratio = 0.46 m2/m3 Orientation: S/N

Net dimensions of heated volume =45 x 60 x 7 m

(U shape) Net floor area of heated zones = 3500 m2 Area of S façade = 752.5 m2 Area of E façade = 315 m2 Area of N façade = 752.5 m2 Area of W façade = 315 m2 Area of Roof = 1750 m2 Area of Basement = 1750 m2 Window area on S façade = 32% Window area on E façade = 22% Window area on N façade = 29% Window area on W façade = 40%

Inte

rnal

g

ain

s People design level = 5.6 m2/people Lighting design level = 12 W/m2 Appliances design level = 1.75 W/m2

Tab. 8: Variable characteristics of the school model.


Bu

ildin

g t

ech

no

log

ies


A A C B A B B A

Typical ACH rate:

0.94 1.13 0.75 1.51 1.13 0.94 1.51 0.94 h‐1

U value of wall =

1.37 1.17 1.34 2.59 1.17 1.41 1.42 0.62 W/m2K

U value of roof =

2.19 1.57 0.72 1.50 1.57 0.63 0.88 0.43 W/m2K


2.56 1.74 1.10 1.24 1.74 3.93 1.14 0.70 W/m2K

U value of glass =

5.70 5.70 2.40 3.00 5.00 2.90 2.90 2.00 W/m2K

g value of glass =

0.89 0.89 0.75 0.80 0.85 0.80 0.80 0.70 -

Passive strategies:


A: Hollow brick, air gap or insulation, concrete, plaster

B: Concrete, insulation, plaster



22

1.3 Reference climatic contexts

In order to calculate, with stationary, quasi-stationary or dynamic calculation methods the energy and comfort performances of buildings, climatic conditions are usually repre-sented as sets of data that describe at different degrees of detail, an “average” climate at a certain location. Since there are a number of weather variables that affect building behaviour it is not straightforward to establish a definition of “average” weather. Different definitions and hence different types of data sets are available (IWEC, TRY, TMY, Me-teonorm, etc.) based on different weighting of the parameters and other choices. Weather data sets can be in the form of a year of hourly data (8 760 hours) synthesized to represent long-term statistical trends and patterns and are used for hourly calculations of energy and power demand of a building.

As performing building simulations for every Entranze Target Country would have been be time consuming (compared to our resources) it has been decided to select 10 key climatic conditions within this European area. As reference indicators have been used the Winter Severity Index and the Summer Severity Index proposed by F. Sanchez de la Florthe (2005), as well the Climatic Cooling Potential by Artmann (2007). We calculated this indexes for 25 cities, within the Entranze Target Countries, selected in function of the nominal climatic characteristics, the availability of homogeneous climatic data (IWEC6) and their relevance (in terms of urban population).

6 The International Weather for Energy Calculations (IWEC) are the result of ASHRAE Research Project

1015 by Numerical Logics and Bodycote Materials Testing Canada for ASHRAE Technical Committee 4.2 Weather Information. The IWEC data files are 'typical' weather files suitable for use with building energy simulation programs, derived from up to 18 years of DATSAV3 hourly weather data.


23

Fig. 8: SCS versus WCS for 25 European cities.

Fig. 9: SCS versus CCP for 25 European cities.

Summer Severity Index versus Winter Severity Index for 25 European cities (within the Entranze Target Countries)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0 0.5 1.0 1.5

WCS

SC

S

Helsinki Munich Prague Innsbruck Vien Bucharest SofiaBerlin Milan Costanta Dusseldorf Lyon Varna ParisMadrid Bordeaux Marseille Foggia Rome Barcelona GenovaBilbao La Coruna Sevilla Palermo

Summer Severity Index versus Climatic Cooling Potential (in July) for 25 European cities (within the Entranze Target Countries)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0 0.5 1.0 1.5 2.0 2.5

CCP

SC

S

Helsinki Munich Prague Innsbruck Vien Bucharest SofiaBerlin Milan Costanta Dusseldorf Lyon Varna ParisMadrid Bordeaux Marseille Foggia Rome Barcelona GenovaBilbao La Coruna Sevilla Palermo


24

Analysing the data obtained we selected as key climatic conditions those of: Seville (ES), Madrid (ES), Rome (IT), Milan (IT), Bucharest (RO), Vienna (AT), Paris (FR), Prague (CZ), Berlin (DE), Helsinki (FI).

Tab. 9: Characterisation of the 10 selected climates. Context Climatic characterisation Relevance

Seville (ES) Mediterranean climate (hot summer subtype) with very low climatic cooling potential (extreme summer conditions)

Medium

Madrid (ES) Semi-arid climate with low climatic cooling potential High

Rome (IT) Mediterranean climate (warm summer subtype) with medium climatic cooling potential

High

Milan (IT) Humid subtropical climate with medium climatic cooling potential

High

Bucharest (RO) Humid continental (hot summer subtype) / Subarctic climate with medium climatic cooling potential

High

Vienna (AT) Humid continental climate (warm summer subtype) with high climatic cooling potential

High

Paris (FR) Oceanic climate with very high climatic cooling po-tential

High

Prague (CZ) Humid continental climate (warm summer subtype) with high climatic cooling potential

High

Berlin (DE) Humid continental climate (warm summer subtype) with high climatic cooling potential

High

Helsinki (FI) Humid continental / Subarctic climate (extreme win-ter conditions)

Medium


25

Fig. 10: Key and secondary weather conditions selected for the Task2.2 and WP3 activities.


26

2. Calculation of energy needs using the EnergyPlus tool

The simulation/calculation campaign has been carried out within the EnergyPlus dy-namic simulation environment (version 7.0-7.2) and applying the Standard EN 15316-3-1 for estimating the DHW demand.

For obtaining building envelopes fully comparable in terms of comfort performance (in-door comfort), the energy need for all the building variants are calculated assuming the same indoor conditions for each typology:

- the same operative temperature and relative humidity setpoints: o residential buildings: 20°C in winter and 26°C in summer (latent control

not applied); o tertiary buildings: 21°C and 30% in winter; 26°C and 70% in summer.

- the same values of minimum air change (at maximum occupation rate), coherent with the assumed occupation levels and the ventilation rates proposed by EN15251 for very low-polluted buildings:

o 0.5 h-1 in the residential buildings; o 0.8 h-1 in the office building; o 1.6 h-1 in the school.

The results obtained are shown in the following paragraphs in terms of monthly [kWh/m2] and hourly [Wh/m2] energy need for heating, cooling and DHW.


27

2.1 Single house

2.1.1 Seville (ES)

Figure 11: Monthly energy needs for heating, cooling and DHW of the single

house located in Seville.

Figure 12: Hourly energy needs for heating and cooling of the single house located

in Seville.


28

2.1.2 Madrid (ES)

Figure 13: Monthly energy needs for heating, cooling and DHW of the single house

located in Madrid.

Figure 14: Hourly energy needs for heating and cooling of the single house locat-

ed in Madrid.


29

2.1.3 Rome (IT)


located in Rome.


ed in Rome.


30

2.1.4 Milan (IT)


located in Milan.


ed in Milan.


31

2.1.5 Bucharest (RO)


located in Bucharest.


ed in Bucharest.


32

2.1.6 Vienna (AT)


located in Vienna.


ed in Vienna.


33

2.1.7 Paris (FR)


located in Paris.


ed in Paris


34

2.1.8 Prague (CZ)


located in Prague.


ed in Prague.


35

2.1.9 Berlin (DE)


located in Berlin.


ed in Berlin.


36

2.1.10 Helsinki (FI)


located in Helsinki.


ed in Helsinki.


37

2.2 Apartment block

2.2.1 Seville (ES)

Figure 31: Monthly energy needs for heating, cooling and DHW of the apartment

block located in Seville.


block located in Seville


38

2.2.2 Madrid (ES)


block located in Madrid.


block located in Madrid.


39

2.2.3 Rome (IT)


block located in Rome.


block located in Rome.


40

2.2.4 Milan (IT)


block located in Milan.


block located in Milan.


41



block located in Bucharest.


block located in Bucharest.


42

2.2.6 Vienna (AT)


block located in Vienna.


block located in Vienna.


43

2.2.7 Paris (FR)


block located in Paris.


block located in Paris.


44

2.2.8 Prague (CZ)


block located in Prague.


block located in Prague.


45

2.2.9 Berlin (DE)


block located in Berlin.


block located in Berlin.


46


Figure 49: Monthly energy needs for heating, cooling and DHW of the apartment block located in Helsinki.


block located in Helsinki.


47

2.3 Office

2.3.1 Seville (ES)

Figure 51: Monthly energy needs for heating, cooling and DHW of the office build-

ing located in Seville.

Figure 52: Hourly energy needs for heating and cooling of the office building lo-

cated in Seville.


48

2.3.2 Madrid (ES)


ing located in Madrid.


cated in Madrid.


49

2.3.3 Rome (IT)


ing located in Rome.


cated in Rome.


50

2.3.4 Milan (IT)


ing located in Milan.


cated in Milan.


51



ing located in Bucharest.


cated in Bucharest.


52

2.3.6 Vienna (AT)


ing located in Vienna.


cated in Vienna.


53

2.3.7 Paris (FR)


ing located in Paris.


cated in Paris.


54

2.3.8 Prague (CZ)


ing located in Prague.


cated in Prague.


55

2.3.9 Berlin (DE)


ing located in Berlin.


cated in Berlin.


56



ing located in Helsinki.


cated in Helsinki.


57

2.4 School

2.4.1 Seville (ES)

Figure 71: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Seville.

Figure 72: Hourly energy needs for heating and cooling of the school located in Seville.


58

2.4.2 Madrid (ES)

Figure 73: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Madrid.

Figure 74: Hourly energy needs for heating and cooling of the school located in Madrid.


59

2.4.3 Rome (IT)

Figure 75: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Rome.

Figure 76: Hourly energy needs for heating and cooling of the school located in Rome.


60

2.4.4 Milan (IT)

Figure 77: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Milan.

Figure 78: Hourly energy needs for heating and cooling of the school located in Milan.


61


Figure 79: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Bucharest.

Figure 80: Hourly energy needs for heating and cooling of the school located in Bucharest.


62

2.4.6 Vienna (AT)

Figure 81: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Vienna.

Figure 82: Hourly energy needs for heating and cooling of the school located in Vienna.


63

2.4.7 Paris (FR)

Figure 83: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Paris.

Figure 84: Hourly energy needs for heating and cooling of the school located in Paris


64

2.4.8 Prague (CZ)

Figure 85: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Prague.

Figure 86: Hourly energy needs for heating and cooling of the school located in Prague


65

2.4.9 Berlin (DE)

Figure 87: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Berlin.

Figure 88: Hourly energy needs for heating and cooling of the school located in Berlin.


66


Figure 89: Monthly energy needs for heating, cooling and DHW of the school lo-cated in Helsinki.

Figure 90: Hourly energy needs for heating and cooling of the school located in Helsinki.


67

2.5 Summary

Table 10: Summary of simulated energy needs for heating, cooling and DHW for the single house base cases.

Sin

gle

Ho

use

Target Country

Reference weather

end-use Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual TOTAL EN

ES Seville Heating 11,2 6,2 2,6 1,5 0,1 0,0 0,0 0,0 0,0 0,1 5,2 9,8 36,7

123,7 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 14,0 25,4 20,7 12,8 0,0 0,0 0,0 72,9 DHW 1,2 1,1 1,2 1,2 1,2 1,2 1,2 1,2 1,2 1,2 1,2 1,2 14,1

ES Madrid Heating 25,9 18,2 8,5 6,2 0,6 0,0 0,0 0,0 0,0 3,9 14,0 26,6 103,9

166,4 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 8,2 19,2 15,6 4,7 0,0 0,0 0,0 47,7 DHW 1,3 1,1 1,3 1,2 1,3 1,2 1,3 1,3 1,2 1,3 1,2 1,3 14,8

IT Rome Heating 18,8 11,7 7,3 2,1 0,3 0,0 0,0 0,0 0,0 2,8 7,5 16,7 67,1

127,7 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 8,0 16,5 15,2 6,0 0,0 0,0 0,0 45,8 DHW 1,3 1,1 1,3 1,2 1,3 1,2 1,3 1,3 1,2 1,3 1,2 1,3 14,8

IT Milan Heating 39,9 30,1 14,2 8,0 1,1 0,0 0,0 0,0 0,0 7,2 23,4 37,0 160,9

208,9 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 7,4 14,4 8,7 1,8 0,0 0,0 0,0 32,4 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,6

RO Bucharest Heating 45,5 30,6 21,1 6,6 1,5 0,0 0,0 0,0 1,5 11,7 28,5 42,1 189,1

236,0 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 7,9 13,0 10,1 0,0 0,0 0,0 0,0 31,0 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,9

AT Vienna Heating 43,4 35,5 21,3 10,0 2,1 0,3 0,0 0,0 1,9 12,3 29,2 43,5 199,5

229,9 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 1,2 7,1 6,2 0,0 0,0 0,0 0,0 14,5 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,9

FR Paris Heating 35,1 29,5 21,8 11,6 3,2 0,5 0,0 0,0 2,5 11,6 25,9 34,2 176,0

199,3 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 4,3 3,1 0,0 0,0 0,0 0,0 7,4 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,9

CZ Prague Heating 48,5 40,1 28,0 14,9 5,3 0,0 0,0 0,0 5,2 18,5 35,9 43,0 239,4

260,5 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 1,2 2,1 1,8 0,0 0,0 0,0 0,0 5,2 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,9

DE Berlin Heating 33,4 30,0 21,2 9,5 3,2 0,0 0,0 0,0 2,2 11,4 24,9 32,9 168,7

193,5 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 3,1 3,5 2,2 0,0 0,0 0,0 0,0 8,9 DHW 1,3 1,2 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 1,3 15,9

FI Helsinki Heating 31,2 26,9 20,9 9,8 1,6 0,0 0,0 0,0 4,2 13,3 26,4 31,0 165,2

183,1 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 0,0 1,1 0,0 0,0 0,0 0,0 1,1 DHW 1,4 1,3 1,4 1,4 1,4 1,4 1,4 1,4 1,4 1,4 1,4 1,4 16,8


68

Table 11: Summary of simulated energy needs for heating, cooling and DHW for the apartment block base cases. A

par

tmen

t b

lock

Target Country

Reference weather



83,9 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 6,6 14,5 11,5 7,1 0,0 0,1 0,0 39,8 DHW 1,8 1,7 1,8 1,8 1,8 1,8 1,8 1,8 1,8 1,8 1,8 1,8 21,6


110,7 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 3,2 9,7 8,3 2,1 0,0 0,0 0,0 23,2 DHW 1,9 1,7 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 22,7

IT Rome Heating 11,0 7,2 5,0 1,7 0,2 0,0 0,0 0,0 0,0 1,5 4,1 9,5 40,3

87,7 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 3,4 9,2 8,9 3,0 0,1 0,1 0,0 24,7 DHW 1,9 1,7 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 1,9 22,7

IT Milan Heating 24,9 19,3 9,3 5,2 0,7 0,0 0,0 0,0 0,0 3,9 13,7 23,0 99,9

139,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 3,4 7,4 4,5 0,6 0,0 0,0 0,0 15,9 DHW 2,0 1,8 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 23,8


163,8 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 5,3 8,7 6,6 0,0 0,0 0,0 0,0 20,6 DHW 2,1 1,9 2,1 2,0 2,1 2,0 2,1 2,1 2,0 2,1 2,0 2,1 24,3


162,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 3,9 3,5 0,0 0,0 0,0 0,0 7,4 DHW 2,1 1,9 2,1 2,0 2,1 2,0 2,1 2,1 2,0 2,1 2,0 2,1 24,3

FR Paris Heating 28,7 24,9 18,8 10,3 3,0 0,5 0,0 0,0 2,1 9,2 20,8 27,6 146,0

173,3 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 1,8 1,2 0,0 0,0 0,0 0,0 3,0 DHW 2,1 1,9 2,1 2,0 2,1 2,0 2,1 2,1 2,0 2,1 2,0 2,1 24,3


145,8 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,8 1,4 1,4 0,0 0,0 0,0 0,0 3,6 DHW 2,1 1,9 2,1 2,0 2,1 2,0 2,1 2,1 2,0 2,1 2,0 2,1 24,3


167,5 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 2,2 2,6 1,6 0,0 0,0 0,0 0,0 6,4 DHW 2,1 1,9 2,1 2,0 2,1 2,0 2,1 2,1 2,0 2,1 2,0 2,1 24,3


163,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 0,0 0,8 0,0 0,0 0,0 0,0 0,8 DHW 2,2 2,0 2,2 2,1 2,2 2,1 2,2 2,2 2,1 2,2 2,1 2,2 25,7


69

Table 12: Summary of simulated energy needs for heating, cooling and DHW for the office building base cases. O

ffic

e

Target Country

Reference weather



102,4 kWh/m2 Cooling 0,1 0,3 1,3 1,4 3,3 9,1 18,3 14,8 10,9 4,3 0,5 0,1 64,3 DHW 0,6 0,6 0,6 0,6 0,6 0,6 0,6 0,6 0,6 0,6 0,6 0,6 7,6


138,8 kWh/m2 Cooling 0,0 0,0 0,2 0,5 1,9 5,5 11,7 10,9 4,6 0,8 0,1 0,0 36,2 DHW 0,7 0,6 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 8,3

IT Rome Heating 18,2 12,6 9,3 3,4 0,5 0,0 0,0 0,0 0,0 2,6 7,5 14,9 68,9

136,4 kWh/m2 Cooling 0,0 0,0 0,0 0,0 2,7 9,3 17,1 16,5 10,1 3,5 0,1 0,0 59,2 DHW 0,7 0,6 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 0,7 8,3

IT Milan Heating 30,3 24,8 12,6 6,6 0,9 0,0 0,1 0,0 0,3 4,9 17,0 28,2 125,7

171,3 kWh/m2 Cooling 0,0 0,0 0,0 0,1 1,5 7,9 13,7 9,3 3,9 0,4 0,0 0,0 36,6 DHW 0,8 0,7 0,8 0,7 0,8 0,7 0,8 0,8 0,7 0,8 0,7 0,8 9,0


165,3 kWh/m2 Cooling 0,0 0,0 0,0 0,2 3,4 7,4 12,7 10,1 2,4 1,2 0,0 0,0 37,4 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,3


212,5 kWh/m2 Cooling 0,0 0,0 0,0 0,1 0,8 2,0 5,7 4,6 0,3 0,0 0,0 0,0 13,5 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,3

FR Paris Heating 32,0 28,4 22,2 12,2 3,5 0,8 0,1 0,1 2,5 11,1 23,7 30,8 167,4

186,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,3 1,6 3,8 3,5 0,5 0,1 0,0 0,0 9,9 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,3


206,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,8 1,0 2,0 2,2 0,2 0,0 0,0 0,0 6,1 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,3


170,2 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,5 2,3 3,0 2,5 0,4 0,0 0,0 0,0 8,7 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,3


259,6 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,1 0,4 2,3 1,8 0,0 0,0 0,0 0,0 4,7 DHW 0,9 0,8 0,9 0,8 0,9 0,8 0,9 0,9 0,8 0,9 0,8 0,9 10,2


70

Table 13: Summary of simulated energy needs for heating, cooling and DHW for the school building base cases. S

cho

ol

Target Country

Reference weather



98,3 kWh/m2 Cooling 0,0 0,0 0,1 0,4 1,6 8,4 19,4 2,2 10,7 2,6 0,2 0,0 45,6 DHW 0,8 0,7 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 0,8 9,7


137,5 kWh/m2 Cooling 0,0 0,0 0,0 0,1 0,6 4,2 11,7 1,0 3,4 0,1 0,0 0,0 21,2 DHW 0,9 0,8 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 10,6

IT Rome Heating 20,5 16,7 12,2 6,0 1,0 0,0 0,0 0,0 0,0 3,3 10,3 14,3 84,4

135,1 kWh/m2 Cooling 0,0 0,0 0,0 0,0 1,4 8,0 18,1 0,8 9,0 2,5 0,2 0,0 40,1 DHW 0,9 0,8 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 0,9 10,6

IT Milan Heating 36,6 32,4 17,5 11,5 1,9 0,1 0,1 0,0 0,5 8,6 23,4 31,2 163,9

198,9 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,5 6,7 13,5 0,3 2,4 0,1 0,0 0,0 23,5 DHW 1,0 0,9 1,0 0,9 1,0 0,9 1,0 1,0 0,9 1,0 0,9 1,0 11,6


175,1 kWh/m2 Cooling 0,0 0,0 0,0 0,0 2,0 5,5 11,7 0,1 1,2 0,5 0,0 0,0 21,0 DHW 1,0 0,9 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 11,9


259,1 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,3 1,4 4,5 0,0 0,1 0,0 0,0 0,0 6,4 DHW 1,0 0,9 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 11,9

FR Paris Heating 32,9 31,1 23,5 15,7 5,2 1,5 0,2 0,0 3,4 13,8 26,3 28,7 182,3

197,9 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,1 0,6 2,6 0,0 0,3 0,0 0,0 0,0 3,6 DHW 1,0 0,9 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 11,9


226,0 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,2 0,3 0,9 0,0 0,0 0,0 0,0 0,0 1,4 DHW 1,0 0,9 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 11,9


231,8 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,1 1,5 1,3 0,0 0,1 0,0 0,0 0,0 3,0 DHW 1,0 0,9 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 11,9


241,1 kWh/m2 Cooling 0,0 0,0 0,0 0,0 0,0 0,0 1,1 0,0 0,0 0,0 0,0 0,0 1,2 DHW 1,1 1,0 1,1 1,1 1,1 1,1 1,1 1,1 1,1 1,1 1,1 1,1 13,1


71

3. Comparison of the EnergyPlus results with the simply hourly EN13790 and INVERT/EE-Lab approach

In this chapter we compare the energy needs for heating and cooling of different build-ings (and climate zones), which we derived from three different calculation tools:

Energy plus, applying a full dynamical approach (only sensible cooling loads) A simple hourly three-nodes model implemented as a spreadsheet tool (in ac-

cordance with the EN 13790) INVERT/EE-Lab Model with the underlying quasi-steady-state monthly energy

balance approach Due to the different calculation approach and the different degree of the complexity of the building and usage description in the three simulation tools, the energy needs vary.

Although the three models are using the same raw climate data, a different im-plementation of converting solar radiation on a horizontal plane into a specifi-cally oriented vertical plane, result in deviating solar gains. In order to reduce these effects, we used the solar radiation data derived by the EN 13790 spread-sheet tool also for the INVERT/EE-Lab calculations. However they do not ex-actly match with those used for the EnergyPlus calculations.

The EnergyPlus model calculates dynamic solar energy transmittances values (g-values) depending on the orientation, date and time. The EN 13790 spread-sheet tool is able to distinguish between orientation-depending g-values, in the INVERT/Model a single value per building needs to be defined.

The results from the EnergyPlus model are derived using a complex ventilation control, which dynamically varies the ventilation rate depending on indoor air condition and present number of persons per square meter. In addition, deviat-ing ventilation rates were defined for different usage types of rooms (e.g. class-rooms, offices, conference rooms, aisles, stairways, baths, etc.). In the applied EN 13790 spreadsheet tool the ventilation rate can be hourly distinguished (for the whole building), in the INVERT/EE-Lab model the ventilation rate distin-guishes between day and night times, non-using hours on using days and non-using days.

The applied shading schedule in the EnergyPlus model depends on the room depended indoor – light intensity. In the two other tools a static approach using default values is used. The same holds for the internal gains due to lighting. In the two other models, the internal gains are fixed and independent from the heating or cooling needs of the building at a given time period.

The EN 13790 spreadsheet tool doesn’t distinguish between using and non-us-ing days. This is one of the main reason, why the results from this tool for build-ings which aren’t used every day significantly deviate from those derived with the two other tools.

For the non-commercial buildings (offices and schools) the EnergyPlus results are also including the latent heat (although it changes results only slightly), for all other results the sensible heat is considered only.

In contrast to the dynamic approaches using thermal coupled nodes, in the quasi steady-state method the same indoor temperature (set temperature) is used for all relevant com-ponents such as: air, wall indoor surface temperature or indoor surface temperature of


72

windows. However, under conditions where heating is required, the indoor surface tem-peratures of walls (and windows) are (assuming constant indoor air temperatures) usu-ally lower than the air temperature. In order to get some sort of effective temperature that reflects the thermal comfort, an operative temperature is defined opair + 0.7s (EN 13790). For the calculations using the EnergyPlus and the EN 13790 spreadsheet tool, the indoor air temperature air is used as set temperature. However, when compar-ing the quasi-steady-state approach (as used in the INVERT/EE-Lab model) with thermal coupled nodes models, rather the operative temperature op than the air temperature air corresponds to the temperature defined in the simplified approach. For the subsequent comparison, we applied the operative temperature calculated using the EN 13790 spreadsheet tool as set temperature in the INVERT/EE-Lab model and not the air tem-perature as done by the two other models.


73

3.1 Single house

Figure 91: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for single house, Seville and Madrid.

Figure 92: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for single house, Rome and Milan.

0

10

20

30

40

50

60

70

80

0

5

10

15

20

25

30

35

40

Annual Energy needs (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: SFH Seville (SP)Energy plus

EN13790 (simple hourly)

INVERT/EE‐Lab (monthly)

Energy plus



Heating

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Madrid (SP)Energy plus



Energy plus



Heating

Cooling

0

25

50

75

100

125

150

175

200

225

250

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Milan (IT)Energy plus



Energy plus



Heating

Cooling

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Rome (IT)Energy plus



Energy plus



Heating

Cooling


74

Figure 93: Comparison of monthly energy needs for heating and cooling (only sen-sible component between Energy Plus, EN13790 and INVERT/EE-Lab calculations for single house, Bucharest and Vienna.

Figure 94: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for single house, Paris and Prague.

0

20

40

60

80

100

120

140

160

180

200

220

240

0

5

10

15

20

25

30

35

40

45

50

55

60


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Bucharest (RO)Energy plus



Energy plus



Heating

Cooling

0

25

50

75

100

125

150

175

200

225

250

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Vienna (AT)Energy plus



Energy plus



Heating

Cooling

0

30

60

90

120

150

180

210

240

270

300

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Prague (CZ)Energy plus



Energy plus



Heating

Cooling

0

20

40

60

80

100

120

140

160

180

200

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Paris (FR)Energy plus



Energy plus



Heating

Cooling


75

Figure 95: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for single house, Berlin and Helsinki.

0

25

50

75

100

125

150

175

200

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Berlin (GE)Energy plus



Energy plus



Heating

Cooling

0

25

50

75

100

125

150

175

200

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: SFH Helsinki (FI)Energy plus



Energy plus



Heating

Cooling


76

3.2 Apartment block

Figure 96: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for apartment block, Seville and Madrid.

Figure 97: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for apartment block, Rome and Milan.

0

15

30

45

60

75

90

0

5

10

15

20

25

30

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Madrid (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

10

20

30

40

50

60

0

5

10

15

20

25

30

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Seville (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

10

20

30

40

50

60

0

5

10

15

20

25

30

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Rome (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Milan (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling


77

Figure 98: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for apartment block, Bucharest and Vienna.

Figure 99: Comparison of monthly energy needs for heating and cooling (only sen-sible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for apartment block, Paris and Prague.

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Bucharest (RO)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Vienna (AT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy need

s (kWh/m

².month)

Comparison: AB Prague (CZ)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

25

50

75

100

125

150

175

200

0

5

10

15

20

25

30

35

40


².a)

Energy need

s (kWh/m

².month)

Comparison: AB Paris (FR)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling


78

Figure 100: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for apartment block, Berlin and Helsinki.

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40

Annual Energy need

s (kWh/m

².a)

Energy needs (kWh/m

².month)

Comparison: AB Helsinki (FI)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy need

s (kWh/m

².month)

Comparison: AB Berlin (GE)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling


79

3.3 Office

Figure 101: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for office, Seville and Madrid.

Figure 102: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for office, Rome and Milan.

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Madrid (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Seville (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Milan (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

15

30

45

60

75

90

0

5

10

15

20

25

30


².a)

Energy needs (kWh/m

².month)

Comparison: Office Rome (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling


80

Figure 103: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for office, Bucharest and Vienna.

Figure 104: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for office, Paris and Prague.

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Bucharest (RO)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

180

200

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: Office Vienna (AT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

180

200

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: Office Prague (CZ)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

25

50

75

100

125

150

175

200

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Paris (FR)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling


81

Figure 105: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for office, Berlin and Helsinki.

3.4 School

Figure 106: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for school, Seville and Madrid.

0

25

50

75

100

125

150

175

200

225

250

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: Office Helsinki (FI)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: Office Berlin (GE)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Cooling

0

15

30

45

60

75

90

105

120

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: School Madrid (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin

0

15

30

45

60

75

90

0

5

10

15

20

25

30


².a)

Energy needs (kWh/m

².month)

Comparison: School Seville (SP)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin


82

Figure 107: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for school, Rome and Milan.

Figure 108: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for school, Bucharest and Vienna.

0

20

40

60

80

100

120

140

160

180

200

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: School Milan (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin

0

15

30

45

60

75

90

0

5

10

15

20

25

30


².a)

Energy needs (kWh/m

².month)

Comparison: School Rome (IT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin

0

20

40

60

80

100

120

140

160

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: School Bucharest (RO)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin

0255075100125150175200225250275300

051015202530354045505560


².a)

Energy needs (kWh/m

².month)

Comparison: School Vienna (AT)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin


83

Figure 109: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for school, Paris and Prague.

Figure 110: Comparison of monthly energy needs for heating and cooling (only sensible component) between Energy Plus, EN13790 and INVERT/EE-Lab calculations for school, Berlin and Helsinki.

0

25

50

75

100

125

150

175

200

225

250

0

5

10

15

20

25

30

35

40

45

50

Annual Energy nee

ds (kWh/m

².a)

Energy nee

ds (kWh/m

².month)

Comparison: School Prague (CZ)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coolin

0

25

50

75

100

125

150

175

200

0

5

10

15

20

25

30

35

40

Annual Energy nee

ds (kWh/m

².a)

Energy nee

ds (kWh/m

².month)

Comparison: School Paris (FR)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coolin

0

30

60

90

120

150

180

210

240

0

5

10

15

20

25

30

35

40


².a)

Energy needs (kWh/m

².month)

Comparison: School Helsinki (FI)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin

0

25

50

75

100

125

150

175

200

225

250

0

5

10

15

20

25

30

35

40

45

50


².a)

Energy needs (kWh/m

².month)

Comparison: School Berlin (GE)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)Energy plusEN13790 (simple hourly)INVERT/EE‐Lab (monthly)

Heatin

Coo

lin


84

3.5 Conclusion

In general we observe that the simply hourly EN13790 as well as the quasi-steady-state method result in the same energy needs for heating as the full dynamical approach ap-plied by the EnergyPlus model. Based on the comparison shown above, we conclude that the more simplified tools tend to over-estimate the energy needs for cooling, espe-cially for office building types located in a Mediterranean climate (Spain and Italy).

These discrepancies may be attributed to:

- slight modelling differences (particularly about the building geometry, the sched-ules of internal gains and the air infiltrations) due to the descriptive simplifications adopted by the INVERT/EE-Lab, the EN13790 method, and the Energy Plus soft-ware;

- the simplified calculation of the solar gains and of the capacitive behaviour of the building components carried out by the EN13790 semi-stationary method, more significant in warm climatic regions.

In some cases, the buildings models have an energy need for heating in summer periods or cooling needs in spring and fall. This is due to the fact that in the models we did not impose periods of heating or cooling, but both may require energy for heating or cooling when the temperatures are below or above the defined set-point temperatures. This can arise from two effects:

a heating demand occurs during night time (or in the morning), the cooling de-mand during day time (afternoon). For such a situation, the EnergyPlus calcula-tions results in a heating and cooling demand. The applied EN13790 spreadsheet tool sums up the hourly results to get the daily energy need, thus the cooling and heating needs partly cancel out each other, which appear to be the more realistic case (pre-cooling strategy).

heating and cooling demands occur on different days within the same month, and thus they do not cancel out each other. Since the applied EN13790 spreadsheet tool uses a typical day per month, such a situation cannot be analysed using this tool.

The monthly quasi-steady-state approach derives the energy needs for heating and cool-ing using utilization factors for gains (cooling) or losses (heating). Thus, such an ap-proach explicitly allows for heating and cooling situations within the same month. The comparison of the results show that EnergyPlus typically results in higher energy needs for heating within the transition periods.

Considering the huge data effort requested for calculations with dynamic tools such as EnergyPlus and the limited availability and large uncertainty of those data for large build-ing stocks, we conclude that simplified models results are sufficient for the focus of this


85

project and the analyses of the evolution of the energy needs and consumption for heat-ing and cooling in different countries.


86

References

F.J. Sanchez de la Flora, J.M. Salmeron Lissen, S. Alvarez Domınguez, A new meth-odology towards determining building performance under modified outdoor con-ditions, Building and Environment 41 (2006) 1231–1238.

N. Artmann, H. Manz, P. Heiselberg, 2007, Climatic potential for passive cooling of build-ings by night-time ventilation in Europe, in Applied Energy 84 (2007) 187–201.

Documents

Heating and cooling energy demand and loads for building ... · PDF fileHeating and cooling energy demand and loads for building types in different countries of the EU ... The loads