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Influence of probabilistic climate projections on building energy simulation

Smith, S. T. ORCID: https://orcid.org/0000-0002-5053-4639, Goodess, C. M., Hacker, J. N., Hanby, V. I., Harpham, C., Jones, P. and Wright, A. J. (2009) Influence of probabilistic climate projections on building energy simulation. In: CISBAT Conference: Renewables in a Changing Climate - from Nano to Urban, September 2009, Lausanne, Switzerland.

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Official URL: http://cisbat.epfl.ch/aboutcisbat.php

Abstract/Summary

The Chartered Institute of Building Service Engineers (CIBSE) produced a technical memorandum (TM36) presenting research on future climate impacting building energy use and thermal comfort. One climate projection for each of four CO2 emissions scenario were used in TM36, so providing a deterministic outlook. As part of the UK Climate Impacts Programme (UKCIP) probabilistic climate projections are being studied in relation to building energy simulation techniques. Including uncertainty in climate projections is considered an important advance to climate impacts modelling and is included in the latest UKCIP data (UKCP09). Incorporating the stochastic nature of these new climate projections in building energy modelling requires a significant increase in data handling and careful statistical interpretation of the results to provide meaningful conclusions. This paper compares the results from building energy simulations when applying deterministic and probabilistic climate data. This is based on two case study buildings: (i) a mixed-mode office building with exposed thermal mass and (ii) a mechanically ventilated, light-weight office building. Building (i) represents an energy efficient building design that provides passive and active measures to maintain thermal comfort. Building (ii) relies entirely on mechanical means for heating and cooling, with its light-weight construction raising concern over increased cooling loads in a warmer climate. Devising an effective probabilistic approach highlighted greater uncertainty in predicting building performance, depending on the type of building modelled and the performance factors under consideration. Results indicate that the range of calculated quantities depends not only on the building type but is strongly dependent on the performance parameters that are of interest. Uncertainty is likely to be particularly marked with regard to thermal comfort in naturally ventilated buildings.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:30113

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