期刊
BUILDING AND ENVIRONMENT
卷 87, 期 -, 页码 342-350出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2014.12.016
关键词
Large-scale retrofit analysis; Bayesian calibration; Normative model; Uncertainty analysis
资金
- US Department of Energy [DE-AC02-06CH11357]
The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustrates both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.
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