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High throughput computing based distributed genetic algorithm for building energy consumption optimization
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DOI：10.1016/j.enbuild.2014.02.053.png)
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Abstract
En 中文
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. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Simulation-based optimization
Building energy optimization
EnergyPlus
GA
Parallel
Distribute
HTCondor
SiPESC.OPT
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