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《East China Electric Power》 2007-11
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PMU optimization configuration based on improved genetic simulated annealing algorithm

TIAN Wei,WANG Hong-xi,SUN Tie-jun(Beihua Univ.,Jilin 132021,China)  
The merits and demerits of the genetic algorithm(GA) and the simulated annealing(SA)algorithm are analyzed,and the improved genetic simulated annealing(MGASA)algorithm,which combines GA with good global optimization performance and SA with strong local optimization ability, was used to optimize PMU configuration with the purpose of complete observability of power system situation and minimum PMU amounts.In MGASA,the genetic operation was conducted for every generation colony first and then the simulated annealing operation was carried out for each individual of the newly-generated colony.Meanwhile,the optimal saving strategy was implemented during the process of selection,crossover,mutation and replication operations,and the replication strategy adopted Metropolis criteria.The IEEE 14-bus and IEEE 39-bus systems were used to examine MGASA and results show that it has good optimization performance and efficiency in PMU configuration.
【Fund】: 吉林省教育厅科研计划项目(200688)
【CateGory Index】: TP18;TM76
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