David R. S. Williams
Centre for Environmental Strategy, Faculty of Engineering and Physical Sciences, University of Surrey, UK
Lucia Elghali
Parsons Brinckerhoff, Westbrook Mills, UK
Russel C. Wheeler
Download articlehttp://dx.doi.org/10.3384/ecp110572056Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden
Linköping Electronic Conference Proceedings 57:41, p. 2056-2063
Published: 2011-11-03
ISBN: 978-91-7393-070-3
ISSN: 1650-3686 (print), 1650-3740 (online)
Compliance with building codes in many countries requires energy simulation of designs in local climate conditions. However; over a building’s lifespan; weather conditions may alter considerably due to climate change. There is a risk therefore that a future climate may alter lifecycle heating and cooling demands from those experienced today. The development of ‘stochastic weather generators’ provides an opportunity to produce synthetic weather data representative of a future climate. These models are calibrated against observed data; before being refitted to the climate change projections of global circulation models. The generator’s output is thousands of years of weather data for a particular future time period. Theoretically these outputs would be appropriate for building energy demand simulation; although analysis of such a high number of projected years would be impractical. This research has developed a method whereby a unique energy “fingerprint” is created for a building and used to estimate heating and cooling demands without the requirement for hours of computation. Energy demand estimates from the fingerprint have been crosschecked with dynamic simulation; indicating a high degree of correlation. The weather generator utilised in this study has been produced by the UK Climate Impact Programme (UKCIP) and is freely available on-line.
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