Uncertainties in predicting the impact of climate change on thermal performance of domestic buildings in the UK

Abstract

Buildings typically have a long life span, which can easily reach 50 or 100 years. In the light of expected climate change it is therefore important to look towards the future, and to analyse how buildings will cope with the changes in climate that are predicted by the climatologists. In such long-term predictions of building performance, uncertainties play a large role.

This paper describes a preliminary study that aims to better map out the consequences of dealing with a whole range of uncertainties in the specific case of predicting the effect of climate change on the energy use and thermal comfort (overheating) in the large stock of terraced houses in the UK. Uncertainties in climate change prediction are compared with other variable factors like building occupancy patterns, actual thickness of construction materials and HVAC control settings. Uncertainties have been propagated in a transient model of these terraced houses using the transient simulation program EnergyPlus. In order to explore the large range of input variants use has been made of a genetic algorithm. The current search and solution spaces are discussed, putting the impact of climate change in perspective with regards to other changes and developments that might increase or decrease overheating. Overall, the findings indicate that uncertainties in long term thermal performance predictions run high, with standard deviations of over 100%. However, the robustness of the contemporary dwelling design is fortunately high.

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References

Intergovernmental Panel on Climate Change. Climate Change: The Scientific Basis Cambridge: Cambridge University Press, 2001.

Hulme M. , Jenkins G. , Lu X. , Turnpenny J. , Mitchell T. , Jones R. , Lowe J. , Murphy J. , Hassell D. , Boorman P. , McDonald R. , Hill S. Climate Change Scenarios for the United Kingdom: The UKCIP02 Scientific Report . Norwich: Tyndall Centre for Climate Change Research, University of East Anglia, 2002.

United Nations Framework Convention on Climate Change, 1997 . Kyoto Protocol. Retrieved 23 March 2006, from http://unfccc.int/resource/docs/convkp/kpeng.html

Blair T. , 2004. Prime Minister's speech on climate change. Retrieved 22 March 2006, from,www.number10.gov.uk/output/page6333.asp

Lowe R. Preparing the built environment for climate change (editorial). Building Research & Information 2003; 31: 195—9.

Frank Th. Climate change impacts on building heating and cooling energy demand in Switzerland. Energy and Buildings 2005; 37: 1175—85.

Gaterell M. , McEvoy M. The impact of climate change uncertainties on the performance of energy efficiency measures applied to dwellings. Energy and Buildings 2005; 37: 982—95.

Hacker J. , Holmes M. , Belcher S. , Davies G. Climate Change and the Indoor Environment: Impacts and Adaptation London: CIBSE, 2005.

Engineering and Physical Sciences Research Council , 2003a. Building knowledge for a changing climate: the impacts of climate change on the built environment. Retrieved 24 march 2006, from, http://www.ukcip.org.uk/resources/publications

10.

Beausoleil-Morrison I, Bernier M. eds. Proceedings of Building Simulation the Ninth International IBPSA Conference, Montréal, Canada, 15—18 August 2005. CD-ROM, including proceedings of all previous IBPSA Conferences.

11.

Malkawi A. , Augenbroe G. Advanced Building Simulation New York and London: Spon Press, 2004.

12.

de Wit S. , Uncertainty in predictions of thermal comfort in buildings, Ph.D. Thesis, Delft University of Technology, Faculty of Civil Engineering , Delft, The Netherlands, 2001.

13.

Macdonald I. Quantifying the effects of uncertainty in building simulation, Ph.D. Thesis , University of Strathclyde, Department of Mechanical Engineering, Energy Systems Research Unit, Glasgow, UK, 2002.

14.

Breesch H. , Janssens A. Building simulation to predict the performances of natural night ventilation: uncertainty and sensitivity analysis. In Beausoleil-Morisson eds. Building Simulation '05, 9th International IBPSA Conference, Montréal, Canada, 15—18 August 2005, 115—122.

15.

Moon H. , Augenbroe G. A mixed simulation approach to analyze modl growth under uncertainty. In Beausoleil-Morisson eds. Building Simulation '05, 9th International IBPSA Conference, Montréal, Canada, 15—18 August 2005, 785—92.

16.

Augenbroe G. , Park C. Quantification methods of technical building performance. Building Research & Information 2005; 33: 159—72.

17.

Packham I. An interactive visualisation system for engineering design using evolutionary computing, Ph.D. Thesis, University of Plymouth, Plymouth, UK, 2003.

18.

Packham I. , Rafiq Y. , Borthwick MF , Denham S. Interactive visualisation for decision support and evaluation of robustness using evolutionary computing. In 11th International Workshop of the European Group for Intelligent Computing in Engineering (EG-ICE), 31st May to 1st June 2004, Weimar, Germany.

19.

Rafiq Y. , Beck M. , Packham I. , Denham S. Evolutionary Computation and visualisation as decision support tools for conceptual building design (Invited paper). In Topping B. H. V ed. Innovation In Civil and Structural Engineering Computing, chapter 3, pp. 49—74, Saxe-Coburg Publications.

20.

Rafiq Y. , Beck M. , Packham I. Interactive visualisation systems for conceptual building design: a practical approach. In International Conference on Advances in Engineering Structures, Mechanics and Construction, University of Waterloo , Canada, 2006.

21.

Goldberg, D.E. , 1989. Genetic algorithms in Search, Optimization and Machine Learning. Boston: Addison-Wesley Professional.

22.

Deb K. Multi-objective Optimization Using Evolutionary Algorithms Wiley, 2001.

23.

Ashrae. Handbook of Fundamentals. Atlanta, American Society of Heating, Refridgerating and Air-Conditioning Engineers, 2005.

24.

Cibse. Design Data Guide London: The Chartered Institution of Building Services Engineers, 1988.

25.

Belcher S. , Hacker J. , Powell D. Constructing design weather data for future climates. Building Services Engineering Research & Technology 2005; 26: 49—61.

26.

de Wit S. , Augenbroe G. Analysis of uncertainty in building design evaluations and its implications . Energy and Buildings 2002; 34: 951—58.

27.

Wright J. , Alajmi A. The robustness of genetic algorithms in solving unconstrained building optimisation problems. In Ninth International IBPSA Conference , Montréal, Canada, 2005.

28.

Silverman BW Density Estimation. New York: Chapman and Hall, 1986.

29.

Lawrence Berkely National Laboratory. EnergyPlus Manual, 2005.