Optimized parameter selection for assessing building energy efficiency

E. Mocanu, P.H. Nguyen, M. Gibescu, W.L. Kling

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Abstract

This study analyzes the influence of various physical parameters on estimating the heating and cooling load requirements of a building. Building energy models represent an important starting point for research in advanced building systems. In order to determine the most relevant combination of parameters for assessing energy use in buildings, we have created a framework which combines a stochastic classification method, namely a Gaussian Mixture Model, with a combinatorial optimization procedure. The framework was evaluated using a benchmark database consisting of 768 simulated buildings for which annual data on energy demands related to heating and cooling were available. The results show that feature selection is an important phase in developing building models by decreasing the computation time while still allowing for a high accuracy in the prediction of energy demand.
Original languageEnglish
Title of host publicationProceedings of the IEEE Young Researchers Symposium (YRS 2014), 24-25 April 2014, Ghent, Belgium
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Publication statusPublished - 2014
Event7th IEEE Young Researchers Symposium in Electrical Power Engineering (YRS 2014), April 24-25, 2014, Ghent, Belgium - Ghent, Belgium
Duration: 24 Apr 201425 Apr 2014

Conference

Conference7th IEEE Young Researchers Symposium in Electrical Power Engineering (YRS 2014), April 24-25, 2014, Ghent, Belgium
Abbreviated titleYRS 2014
CountryBelgium
CityGhent
Period24/04/1425/04/14
OtherJoint IAS/PELS/PES Benelux Chapter

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