High throughput computing based distributed genetic algorithm for building energy consumption optimization

Yang, Chunfeng, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400, Petri, Ioan ORCID: https://orcid.org/0000-0002-1625-8247, Yuce, Baris ORCID: https://orcid.org/0000-0002-9937-1535, Chen, Biaosong and Jayan, Bejay 2014. High throughput computing based distributed genetic algorithm for building energy consumption optimization. Energy and Buildings 76 , pp. 92-101. 10.1016/j.enbuild.2014.02.053

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Abstract

Simulation based energy consumption optimization problems of complicated building, solved by stochastic algorithms, are generally time-consuming. This paper presents a web-based parallel GA optimization framework based on high-throughput distributed computation environment to reduce the computation time of complex building energy optimization applications. The optimization framework has been utilized in an EU FP7 project - SportE2 (Energy Efficiency for Sport Facilities) to conduct large scale buildings energy consumption optimizations. The optimization results achieved for a testing building, KUBIK in Spain, showed a significant computation time deduction while still acquired acceptable optimal results.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TD Environmental technology. Sanitary engineering T Technology > TH Building construction
Uncontrolled Keywords:	Simulation-based optimization; Building energy optimization; EnergyPlus; GA; Parallel; Distribute; HTCondor; SiPESC.Opt
Additional Information:	Online publication date: 4 March 2014.
Publisher:	Elsevier
ISSN:	0378-7788
Date of Acceptance:	14 February 2014
Last Modified:	25 Oct 2022 09:23
URI:	https://orca.cardiff.ac.uk/id/eprint/58282

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