Following years of research and design in architecture under bio-climatic, sustainable and passive-energy concepts, today’s buildings are often well designed and constructed, responding to determined climate conditions and the user’s requirements for comfort and, in some cases, they are integrated into the urban environment. However, the lifetime of a building can be over 100 years and the climate is changing rapidly. This work investigates the impact of climate change future (2040 and 2070) on the energy consumption of residential buildings recently constructed, under three possible scenarios. The scenarios are created considering a low, medium or strong effect of global warming. Two types of buildings, with comparable consumption results of today, are investigated in three different cities around the world with a multi-zone type 56 of Trnsys simulation tool. At the end of the work, the concepts of energy robustness and global thermal effusivity of buildings are discussed as important strategies to reduce the possible impact of climate change on the built environment. The use of simulation tools to estimate the sensitivity of buildings is also analyzed, taking into consideration the recent goals of applying uncertainty and sensitivity analysis to building performance simulation science.
References
[1]
Pagès, A.; Cuchí, A. Moving the entire building sector towards low CO2 emissions. In Proceedings of the PLEA Conference, Dublin, Ireland, 22–24 October 2008.
[2]
Clarke, J.A. Energy Simulation in Building Design; Butterworth-Heinemann: Oxford, UK, 2001.
[3]
Waltz, J.P. Computerized Building Energy Simulation Handbook; Monticello: New York, NY, USA, 2000.
[4]
Hensen, J.L.M.; Lamberts, R.; Negrao, C.O.R. Building performance simulation at the start of the 3rd millennium. Build. Environ.?2002, 37, 765–767, doi:10.1016/S0360-1323(02)00040-9.
[5]
Crawley, D.B.; Lawrie, L.K.; Winkelmann, F.C.; Buhl, W.F.; Huang, Y.J.; Pedersen, C.O.; Strand, R.K.; Liesen, R.J.; Fisher, D.E.; Witte, M.J.; Glazer, J. EnergyPlus: Creating a new-generation building energy simulation program. Energy Build.?2001, 33, 319–331, doi:10.1016/S0378-7788(00)00114-6.
[6]
Barnaby, C.S.; Crawley, D.B. Weather data for building performance simulation. In Building Performance Simulation for Design and Operation; Routdledge: London, UK, 2011. Chapter 3.
[7]
Jentsch, M.F.; Bahaj, A.S.; James, P.A.B. Climate change future proofing of buildings—Generation and assessment of building simulation weather files. Energy Build.?2008, 40, 2148–2168, doi:10.1016/j.enbuild.2008.06.005.
[8]
De Wilde, P.; Tian, V. Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change. Build. Simul.?2009, 2, 157–174, doi:10.1007/s12273-009-9116-1.
[9]
Taguchi, G. System of Experimental Design; White Plains: New York, NY, USA, 1987.
[10]
Taguchi, G. Introduction to Quality Engineering; White Plains: New York, NY, USA, 1986.
[11]
Taguchi, G. Robust technology development. Mech. Eng.?1993, 3, 60–62.
[12]
Palme, M.; Isalgué, A.; Coch, H.; Serra, R. Robust design: A way to control energy use from human behavior in architectural spaces. In Proceedings of the PLEA Conference, Geneve, Switzerland, 6–8 September 2006.
[13]
Palme, M.; Isalgué, A.; Coch, H.; Serra, R. Energy consumption and robustness of buildings. In Proceedings of the CESB10 Conference, Prague, Czech Republic, 26–28 June 2010.
[14]
Palme, M. Energy Sensitivity of Buildings. Ph.D. Dissertation, Universidad Politécnica de Catalu?a, Barcelona, Spain, 10 March 2010. Available online: http://hdl.handle.net/10803/6140 (accessed on 15 November 2012).
[15]
Zeiler, W.; van Houten, R.; Boxem, G. SMART buildings: Intelligent software agents. In Proceedings of the SEB Conference, Brighton, CO, USA, 29 April–1 May 2009.
[16]
Harputlugil, G.; de Wilde, P.; Hensen, J.; Celebi, G. Development of a thermally robust school outline design for different climate regions of Turkiye. In Proceeding of the IBPSA Building Simulation Conference, Glasgow, UK, 27–30 July 2009.
[17]
IPCC Emissions Scenario Special Report. Available online: http://www.ipcc.ch (accessed on 15 November 2012).
[18]
Neila, F.J. Arquitectura Bioclimática en un Entorno Sostenible (in Spanish); Munilla-Lería Ed.: Madrid, Spain, 2004.
[19]
TRNSYS Manual. Available online: http://www.trnsys.com (accessed on 15 November 2012).
[20]
Climatic Change Weather File Generator Manual, UKCIP Official Site, Available online: http://www.ukcip.com (accessed on 15 November 2012).
[21]
Orehounig, K.; Doppelbauer, E.M.; Madhavi, A.; Loibl, W.; Totzer, T. Climate change, building design, and thermal performance. In Proceedings of the IBPSA Building Simulation Conference, Sydney, Australia, 14–16 November 2011.
[22]
Pagés, A.; Palme, M.; Isalgué, A.; Coch, H. Energy consumption and CO2 emissions in the construction and use of flats according to floor area. In Proceedings of theWREC Congress X, Glasgow, UK, 19–25 July 2009.
[23]
Mara, T.; Tarantola, S. Application of global sensitivity analysis of model output to building thermal simulation. Build. Simul.?2008, 1, 290–302, doi:10.1007/s12273-008-8129-5.
[24]
Serra, R.; Coch, H. Arquitectura y Energía Natural (in Spanish); UPC Edicions: Barcelona, Spain, 1996.
[25]
Saltelli, A.; Chan, K.; Scott, E.M. Sensitivity Analysis; John Wiley and Sons: West Sussex, UK, 2000.
[26]
Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F. Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models; John Wiley and Sons: West Sussex, UK, 2004.
[27]
Saltelli, A.; Tarantola, S. On the relative importance of input factors in mathematical models: Safety assessment for nuclear waste disposal. J. Am. Stat. Assoc.?2002, 97, 702–709, doi:10.1198/016214502388618447.
[28]
Hoffman, F.O.; Hammonds, J.S. Propagation of uncertainty in risk assessments: The need to distinguish between uncertainties due to lack of knowledge and uncertainty due to variability. Risk Anal.?1994, 14, 707–712, doi:10.1111/j.1539-6924.1994.tb00281.x. 7800861
[29]
De Wit, S. Identification of the important parameters in thermal building simulation. J. Stat. Comput. Simul.?1997, 57, 305–320, doi:10.1080/00949659708811814.
[30]
Bruke, K.; Kenny, P.; Finn, D. The transparency and repeatability of building energy performance certification. In Proceedings of the DYNASTEE Conference, Athens, Greece, 14–18 October 2005.
[31]
Clevenger, C.; Haymaker, J. The impact of the building occupant on energy modeling simulation. In Proceedings of the Joint International Conference on Computing and Decision Making in Civil and Building Engineering, Montreal, Canada, 14–16 June 2006.