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

Yang, Chunfeng, Li, Haijiang, Rezgui, Yacine, Petri, Ioan, Yuce, Baris, 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
Computer Science & Informatics
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
Last Modified: 17 Nov 2017 20:28
URI: http://orca-mwe.cf.ac.uk/id/eprint/58282

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Cited 3 times in Web of Science. View in Web of Science.

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