Uncertainty and sensitivity analysis of building performance using probabilistic climate projections: A UK case study

Uncertainty and sensitivity analysis of building performance using probabilistic climate projections: A UK case study. Tian, W. & de Wilde, P. Automation in Construction, 20(8):1096–1109, December, 2011.

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This study explores the uncertainties and sensitivities in the prediction of the thermal performance of buildings under climate change. This type of analysis is key to the assessment of the adaptability and resilience of buildings to changing climate conditions. The paper presents a comprehensive overview of the key methodological steps needed for a probabilistic prediction of building performance in the long term future (50 to 80years). The approach propagates uncertainties in climate change predictions as well as the uncertainties related to interventions in building fabric and systems. A case study focussing on an air-conditioned university building at the campus of the authors is presented in order to demonstrate the methodology. This employs the most recent probabilistic climate change projections for the United Kingdom (UKCP09 dataset) and takes into account facility management uncertainties when exploring uncertainties in the prediction of heating energy, cooling energy, and carbon emissions.

@article{tian_uncertainty_2011,
	title = {Uncertainty and sensitivity analysis of building performance using probabilistic climate projections: {A} {UK} case study},
	volume = {20},
	issn = {0926-5805},
	shorttitle = {Uncertainty and sensitivity analysis of building performance using probabilistic climate projections},
	url = {http://www.sciencedirect.com/science/article/pii/S0926580511000653},
	doi = {10.1016/j.autcon.2011.04.011},
	abstract = {This study explores the uncertainties and sensitivities in the prediction of the thermal performance of buildings under climate change. This type of analysis is key to the assessment of the adaptability and resilience of buildings to changing climate conditions. The paper presents a comprehensive overview of the key methodological steps needed for a probabilistic prediction of building performance in the long term future (50 to 80years). The approach propagates uncertainties in climate change predictions as well as the uncertainties related to interventions in building fabric and systems. A case study focussing on an air-conditioned university building at the campus of the authors is presented in order to demonstrate the methodology. This employs the most recent probabilistic climate change projections for the United Kingdom (UKCP09 dataset) and takes into account facility management uncertainties when exploring uncertainties in the prediction of heating energy, cooling energy, and carbon emissions.},
	language = {en},
	number = {8},
	urldate = {2019-11-28},
	journal = {Automation in Construction},
	author = {Tian, Wei and de Wilde, Pieter},
	month = dec,
	year = {2011},
	keywords = {Building simulation, Climate change, Energy performance, Sensitivity analysis, Uncertainty analysis},
	pages = {1096--1109},
}

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