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

•Computation time of a comprehensive building energy optimization problem has been significantly reduced.•We presented a high throughput computing based distributed genetic algorithm.•The implementation has been utilized in an EU FP7 project – SportE2. 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.