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
|
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: | 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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