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《Electric Power Automation Equipment》 2002-08
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Improved genetic algorithm for reactive power optimization of electric network

REN Zhen 1,ZHONG Hong mei 1,ZHANG Yong jun 1,TANG Zhuo yao 2(1. Department of Electric Power,South China University of Technology,Guangzhou 510641,China; 2. Dispatch Center of Foshan Electric Bureau,Foshan 528000,China)  
Regarding to the low speed of traditional genetic algorithm (TGA) used in real time reactive power optimization in power systems,an improved algorithm,period evolution genetic algorithm (PEGA), is presented.The population size of the group and the maximum evolution generation are no longer fixed.The evolution process is divided into several periods, the group maximum population is increasing gradually and the maximum generation of each period is set accordingly.It can improve the direction in searching optimal solution,prevent the premature convergence of algorithm,and ensure the efficiency of each alternation during latter evolution periods for increasing the calculation speed.The proposed algorithm is evaluated in an IEEE 30 bus power system,the result shows that PEGA has better global searching ability with faster convergence rate and better performance in real time reactive power control.
【Key Words】: reactive power optimization genetic algorithm period evolution
【CateGory Index】: TM761.1
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