• No results found

Simulating and mapping future energy demands for European buildings

N/A
N/A
Protected

Academic year: 2021

Share "Simulating and mapping future energy demands for European buildings"

Copied!
58
0
0

Bezig met laden.... (Bekijk nu de volledige tekst)

Hele tekst

(1)

buildings

Citation for published version (APA):

Schijndel, van, A. W. M., Huijbregts, Z., Martens, M. H. J., & Schellen, H. L. (2014). Simulating and mapping future energy demands for European buildings. In Climate for Culture : Final Expert Meeting July 7-8 2014, Munich, Germany (pp. 1-57)

Document status and date: Published: 01/01/2014

Document Version:

Accepted manuscript including changes made at the peer-review stage

Please check the document version of this publication:

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.

• The final author version and the galley proof are versions of the publication after peer review.

• The final published version features the final layout of the paper including the volume, issue and page numbers.

Link to publication

General rights

Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain

• You may freely distribute the URL identifying the publication in the public portal.

If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement:

www.tue.nl/taverne Take down policy

If you believe that this document breaches copyright please contact us at: openaccess@tue.nl

providing details and we will investigate your claim.

(2)

Simulating and Mapping Future Energy Demands for European Buildings

A.W.M. (Jos) van Schijndel, Z. (Zara) Huijbregts, M.H.J. (Marco) Martens & H.L. (Henk) Schellen Eindhoven University of Technology

Abstract. In this paper we present simulated results for recent past (RP), near future 2020-2050 (NF)

and far future 2070-2100 (FF) energy demands for European buildings. It is new combination of three recent developments: Firstly, the simulation and mapping of building performance indicators based on European weather stations. Secondly, a multi zone energy model, representing a wide range of buildingss. The latter consists of 16 different building zone types equal to all combinations of 4 levels of buildings construction and 4 levels of climate control. Thirdly, the availability of hourly based, EU wide, external future A1B climate files from the EU FP7 Climate for Culture project. We used 7 performance indicators: (1) mean indoor temperature; (2) mean indoor relative humidity; (3) mean heating demand; (4) mean cooling demand; (5) mean humidification demand; (6) mean dehumidification demand; (7) total energy demand to produce EU maps for 16 building types and five 30 year time periods: RP, NF, FF, NF-RP and FF-RP. This gives in total 560 maps. The most important results are included in this preliminary paper.

1. INTRODUCTION

Due to the climate change debate, a lot of research and maps of external climate parameters are available. However, maps of indoor climate performance parameters are still lacking. This paper presents a methodology for obtaining maps of performances of similar buildings that are virtually spread over whole Europe. The produced maps are useful for analyzing regional climate influence on building performance indicators such as energy use and indoor climate. Our approach is a new combination of three recent developments. Each development is introduced in a separate Section: Firstly, the simulation and mapping of building performance indicators based on European weather stations. Secondly, a multi zone energy model, representing a wide range of buildings. Thirdly, the availability of hourly based, EU wide, external future A1B climate files from the EU FP7 Climate for Culture project.

1.1 The simulation and mapping of building performance indicators based on European weather stations (Schijndel, A.W.M. van & Schellen, H.L., 2013)

This paper presents a methodology and results for obtaining maps of performances of similar buildings that are virtually spread over whole Europe. The whole building model used for the simulations, originates from the thermal indoor climate model ELAN which was already published in 1987 (de Wit et al. 1988). The current hourly-based model HAMBase, is part of the Heat, Air and Moisture Laboratory (HAMLab 2014), and is capable of simulating the indoor temperature, the indoor air humidity and energy use for heating and cooling of a multi-zone building. The physics of

(3)

this model is extensively described by de Wit (2006). An overview of all validation results of the whole building model HAMBase are recently presented in van Schijndel (2014).

1.2 A multi zone indoor climate and energy model, representing a wide range of museums (Martens, M.H.J., 2012)

We summarize Appendix B. This chapter describes the input for the existing simulation model that allows studying all 16 combinations of quality of envelope (QoE) and level of control (LoC). To be able to assess the influence of Quality of Envelope (QoE) and Level of Control (LoC), a typical exhibition room layout (see Figure 1) is put in the simulation model.

Figure 1. A multi zone indoor climate and energy model, representing a wide range of museums

This layout is based on common museum exhibition room specifications as encountered in several of the researched museums; this room is located at a corner of a building. The room consists of a single

(4)

zone, 10m long, 10m wide and with a height of 3.5m. The ceiling, floor, north and east wall are adiabatic, which means that the zone is connected to other zones, identical in behavior, that are not part of the simulation. The south and west wall are external walls and have a window of 5 m² each. In (Martens 2012) a full description of the input for the model is provided. This single zone is put into the model 16 times; for each zone some parameters are changed according to QoE and LoC. These parameters are displayed in table 7.1 and 7.2 of Figure 1. The construction of the building depends on QoE: walls, glazing and infiltration rate (caused by leakages in the envelope) all change when improving the thermal quality of the envelope. Set points depend on LoC. The available capacity for heating, cooling, humidification and dehumidification is set to an unrealistically high value to make sure set points are actually achieved; this is deliberately chosen to stress the influence on energy use. All 16 types were implemented into one single multi-zone HAMBase model, thus providing a very efficient way of simulating all variants simultaneously. A year with hourly based external climate values takes less than 10 seconds to run on a 4GB,2.6GHz computer.

1.3 Hourly based, EU wide, external future A1B climate files (Climate for Culture 2014)

During the Climate for Culture project, external climate files were developed especially for building simulation purposes using the REMO model (Jacob and Podzun 1997). Figure 2 shows the grid, where each location covers the A1B external climate for time periods: Recent past (RP) 1960-1990, near future (NF) 2020-2050 and far future (FF) 2070-2100.

Figure 2. The grid, where each location covers the A1B external climate for time periods: Recent past (RP) 1960-1990, near future (NF) 2020-2050 and far future (FF) 2070-2100. The red areas represent extrapolation areas where the results are not accurate.

The red areas represent extrapolation areas where the results are not accurate. All data will become public available by the end of 2014.

(5)

1.4 Goal and outline

The goal of this work is produce EU maps that show the future energy demands for the A1B climate scenario regarding a wide range of types of museums and monumental buildings.

The outline of the paper is as follows: Section 2 presents the methodology. Section 3 shows exemplarily results. In Section 4 we provide the conclusions. The Appendix contains all maps.

2. METHODOLOGY

In this paper we present simulated results for recent past (RP), near future 2020-2050 (NF) and far future 2070-2100 (FF) energy demands for European museums and monumental buildings. A multi zone energy model, representing a wide range of museums and monumental buildings. The latter consists of different 16 building zone types as all combinations of 4 levels of buildings construction and 4 levels of climate control. The different building type 1 through 16 with the corresponding Level of Control (LoC) and Level of Envelope (LoE) are shown in Figure 3 together with a typical result from Martens (2012).

Figure 3. The different building types 1 through 16 with the corresponding Level of Control (LoC) and Level of Envelope (LoE)

We used 7 performance indicators: (1) mean indoor temperature; (2) mean indoor relative humidity; (3) mean heating demand; (4) mean cooling demand; (5) mean humidification demand; (6) mean dehumidification demand; (7) total energy demand to produce EU maps for 16 building types and five 30 year time periods: RP, NF, FF, NF-RP and FF-RP. This gives in total 560 maps.

Interpretation of mean demand is the mean power (W) over a period of 30 years (and thus regardless of the seasons). 1W (J/s) heat demand multiplied with 365x24x3600s equals to annual heating energy of 31536000 J = 31.536 MJ. Please note that in all our models the building volume is

1 5 9 13 2 6 10 14 3 7 11 15 4 8 12 16

(6)

350 m3. So 1W also represents 31.536 MJ/ (year x 350 m3)= 90 kJ/(year x (m3 building volume)) = 2.2510-3 liter oil / (year x (m3 building volume)) ( by using calorific value of 106 J/liter for oil).

1𝑊 ≈𝑦𝑒𝑎𝑟 × 𝑚2 𝑚𝐿 𝑜𝑖𝑙3 𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔

For example 100W and a building volume of 500m3 equals about 100 liter/year.

Furthermore, for all power calculations related with the indoor climate, we assumed perfectly (100% efficiency) air-conditioned HVAC system. The reader should notice that in practical HVAC systems a lot more energy may be required for cooling and dehumidification. For example for dehumidification most systems cool first below dew point and afterwards heat the air to a certain value. Therefore, it is clear, that a lot more energy may be required than just looking at air-sided part of the balance.

3. RESULTS

We use building type 16 i.e. both the highest quality of envelope as well as the highest quality of control and the external climate of the recent past (RP). We start with explaining the seven different types of maps. The reader should notice that each map has its own color scale.

3.1 Seven types of maps

Figure 4 shows the mean indoor temperature:

Figure 4: The mean indoor temperature of building type 16 from 1960-1990 (RP)

Due to the high level of control, the mean indoor temperature is within a small band around 20 oC.

(7)

Figure 5: The mean relative humidity of building type 16 from 1960-1990 (RP)

Again, due to the high level of control the mean relative humidity is within a small band around 50%. The reader should notice that the results on the top left (part of Greenland) and bottom right (near Iraq) are artifacts that are created by extrapolation errors. See also Figure 2.

Figure 6 provides the mean heating power:

Figure 6: The mean heating power of building type 16 from 1960-1990 (RP)

We see as expected the highest heating power at the north part of Europe and the Alps. Again the negative values (see bottom left) are not physical and are created by extrapolation errors.

(8)

Figure 7: The mean cooling power of building type 16 from 1960-1990 (RP)

As expected the most cooling is needed at the south of Europe. Figure 8 presents the mean humidification power:

Figure 8: The mean humidification power of building type 16 from 1960-1990 (RP)

The highest values are located where heating is also needed but also at relative dry external climates.

(9)

Figure 9: The mean dehumidification power of building type 16 from 1960-1990 (RP)

North Italy seems to have quite high values.

Figure 10 shows the mean total power, this equals the ‘sum of’ Figures 6-9.

Figure 10: The mean total climate control power of building type 16 from 1960-1990 (RP)

(10)

3.2 Five different 30 years periods

For all building types we simulated three 30 years period RP, NF, FF and calculated two trends NF-RP, FF-RP providing five 30 year time periods: RP, NF, FF, NF-RP and FF-RP. So for example for building type 16 there are five simulated total air-conditioning power maps:

Figure 11. For building type 16, five simulated total air-conditioning power RP, NF, FF, NF-RP and FF-RP

From Figure 11 it can be seen that it is difficult so derive conclusion from the first three maps (NP, NF & FF). However both trend maps, NF-RP & FF-NP show a good overview what could happen in the future regarding the total air-conditioning power of building type 16. For NF-RP and FF-RP maps, positive values mean more energy demand and negative mean less energy demand in future. (Please note that there is typing error at the titles of FF-NP and NF-NP, this should be FF-RP and NF-RP).

(11)

3.3 Exemplarily results

In Appendix C all maps are presented. 16 building types and five 30 year time periods: RP, NF, FF, NF-RP and FF-NF-RP, gives in total 560 maps. Some of the these maps contain all zero values, for example air conditioning power where there is no heating, cooling and (de)humidification (building types 1,5,9,13), these maps and are left out. This leaves a total of 475 no-zero maps at Appendix C.

An unheated building with a low quality of envelope (building type 1)

What will happen with the indoor temperature and relative humidity inside unheated buildings with a low quality of envelope? See Figure 12.

Figure 12. An unheated building with a low quality of envelope (building type 1)

Regarding the indoor temperature, the highest impact is near the Mediterranean. The mean indoor temperature may raise with 5 oC. The mean relative humidity inside unheated buildings can slightly increase or decrease, dependent on the location.

(12)

A heated building with a low quality of envelope (building type 2)

What will happen with the energy demand and change in relative humidity for heated buildings with a poor building envelope? See Figure 13.

Figure 13. A heated building with a low quality of envelope (building type 2)

Here we see a positive effect: For this building type the energy demand decreases in almost all parts of Europe! This is obvious due the raise of the mean external temperature. Also the mean relative humidity increases. During winter times when it is dry inside, this is also beneficial.

(13)

A fully air-conditioned building with a low quality of envelope (building type 4)

What will happen with the energy demand for a recently built building with high standards for both the building envelope as well as the climate control? See Figure 14.

Figure 14. A fully air-conditioned building with a low quality of envelope (building type 4)

Here we see very big differences in Europe. North Europe and the Alps face a substantial decrease in total power for air-conditioning, while the Mediterranean face a substantial increase. There are also locations around the 50o latitude with unchanged mean total energy demands in the future.

4. CONCLUSIONS

In this paper we present simulated results for recent past (RP), near future 2020-2050 (NF) and far future 2070-2100 (FF) energy demands for European buildings. It is new combination of three recent developments: Firstly, the simulation and mapping of building performance indicators based on European weather stations. Secondly, a multi zone energy model, representing a wide range of buildings. The latter consists of 16 different building zone types equal to all combinations of 4 levels of buildings construction and 4 levels of climate control. Thirdly, the availability of hourly based, EU wide, external future A1B climate files from the EU FP7 Climate for Culture project. We used 7 performance indicators: (1) mean indoor temperature; (2) mean indoor relative humidity; (3) mean heating demand; (4) mean cooling demand; (5) mean humidification demand; (6) mean dehumidification demand; (7) total energy demand to produce EU maps for 16 building types and five 30 year time periods: RP, NF, FF, NF-RP and FF-RP. This gives in total 560 maps. The most important results are included in this preliminary paper.

References

Climate for Culture (2014), http://www.climateforculture.eu

HAMLab (2014), http://archbps1.campus.tue.nl/bpswiki/index.php/Hamlab

Jacob, D. and Podzun, R. (1997). Sensitivity studies with the Regional Climate Model REMO. Meteorology and Atmospheric Physics, 63, pp 119-129.

Larsen X.G., Mann, J., Berg, J., Gottel, H., Jacob, D. (2010). Wind climate from the regional climate model REMO. Wind Energy 13, pp 279-206

(14)

Martens, M.H.J. (2012), Climate risk assessment in museums, PhD Dissertation, Eindhoven University of Technology

Schijndel A.W.M. van (2007). Integrated Heat Air and Moisture Modeling and Simulation, PhD Dissertation, Eindhoven University of Technology

Schijndel, A.W.M. van & Schellen, H.L. (2013). The simulation and mapping of building performance indicators based on european weather stations. Frontiers of Architectural Research, 2, 121-133. Schijndel, A.W.M. van (2014). A review of the application of SimuLink S-functions to multi domain

modeling and building simulation. Journal of Building Performance Simulation, 7(3), 165-178. Wit M.H. de ,H.H. Driessen (1988). ELAN A Computer Model for Building Energy Design. Building and

Environment 23, pp 285-289

Wit, M.H. de, (2006). HAMBase, Heat, Air and Moisture Model for Building and Systems Evaluation, Bouwstenen 100, Eindhoven University of Technology

(15)

Appendix:

(16)
(17)
(18)
(19)
(20)
(21)
(22)
(23)
(24)
(25)
(26)
(27)
(28)
(29)
(30)
(31)
(32)
(33)
(34)
(35)
(36)
(37)
(38)
(39)
(40)
(41)
(42)
(43)
(44)
(45)
(46)
(47)
(48)
(49)
(50)
(51)
(52)
(53)
(54)
(55)
(56)
(57)
(58)

Referenties

GERELATEERDE DOCUMENTEN

Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of

Uit ons onderzoek blijkt dat de eigen houding van verzorgenden en artsen en de manier van communicatie voor een belangrijk deel bepalen waardoor een bewoner antipsychotica krijgt

Recently, an online website, called NeoGuard Information System, has been developed by our research group and consists of three modules: 1) an EEG database, for collecting and

The proposed detection-guided NLMS adaptive partial crosstalk can- celler for DSL targets the dominant crosstalkers across user lines and tones, has low run-time

Section 3.3: We present a point counting algorithm for ordinary elliptic curves over a finite field of characteristic p > 2, based on the computation of the GAGM sequence..

18 Tot_asset Total assets in thousands of euros reported for financial year 2005 Values in other currencies other than euro were translated @ the historical exchange rate of 31

Correlation is significant at the 0.01 level

Of the missions I embarked on last year, none was fraught with as much risk to my office and to the United Nations as Iraq. The peace we seek in Iraq, as everywhere, is one