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《Journal of Beijing University of Aeronautics and Astronautics》 2008-01
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Optimal research of distributed parallel genetic algorithm for reactive power optimization

Liu Keyan Li Yunhua(School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100083,China)Sheng Wanxing(China Electric Power Research Institute,Beijing,100085,China)  
A distributed parallel genetic algorithm based on personal computer(PC) cluster was proposed to solve reactive power optimization,aiming at the disadvantage of traditional genetic algorithm,such as the bad searching quality and long computation time.It adopts the improved genetic simulated annealing algorithm and distributed parallel technique message passing interface(MPI),to implement the distributed computing on PC cluster.The algorithm uses the individual migration strategy to collaboratively optimize every process.The dynamic populations are adopted to balance the computing load.An IEEE 14 test system and a practical power system are tested.The results reveal that the algorithm has a good stable searching capacity and good parallel efficiency.The proposed method can be used to solve the reactive power optimization of large-scale power system.
【Fund】: 国家重点基础研究发展计划资助项目(G1998030405)
【CateGory Index】: TP18;TM714
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