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Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change

  • Research Article/Building Thermal Lighting, and Acoustics Modeling
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Abstract

There is growing concern about the potential impact of climate change on the thermal performance of buildings. Building simulation is well-suited to predict the behaviour of buildings in the future, and to quantify the risks for prime building functions like occupant productivity, occupant health, or energy use. However, on the time scales that are involved with climate change, different factors introduce uncertainties into the predictions: apart from uncertainties in the climate conditions forecast, factors like change of use, trends in electronic equipment and lighting, as well as building refurbishment / renovation and HVAC (heating, ventilation, and air conditioning) system upgrades need to be taken into account. This article presents the application of two-dimensional Monte Carlo analysis to an EnergyPlus model of an office building to identify the key factors for uncertainty in the prediction of overheating and energy use for the time horizons of 2020, 2050 and 2080. The office has mixed-mode ventilation and indirect evaporative cooling, and is studied using the UKCIP02 climate change scenarios. The results show that regarding the uncertainty in predicted heating energy, the dominant input factors are infiltration, lighting gain and equipment gain. For cooling energy and overheating the dominant factors for 2020 and 2050 are lighting gain and equipment gain, but with climate prediction becoming the one dominant factor for 2080. These factors will be the subject of further research by means of expert panel sessions, which will be used to gain a higher resolution of critical building simulation input.

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  1. School of Engineering, Environmental Building Group, University of Plymouth, Reynolds Building, Drake Circus, Plymouth, Devon, PL4 8AA, UK

    Pieter de Wilde & Wei Tian

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  1. Pieter de Wilde
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  2. Wei Tian
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Correspondence to Pieter de Wilde.

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de Wilde, P., Tian, W. Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change. Build. Simul. 2, 157–174 (2009). https://doi.org/10.1007/s12273-009-9116-1

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  • DOI: https://doi.org/10.1007/s12273-009-9116-1

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