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《Electric Power Automation Equipment》 2003-01
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Diversity enhancing genetic algorithm for voltage and reactive power optimization

ZHANG Yong-jun 1 ,REN Zhen 1 ,TANG Zhuo-yao 2 ,SHANG Chun 2 (1.South China University of Technology,Guangzhou510640,China;2.Guangdian Power Grid Group Foshan Branch,Foshan528000,China)  
In the application to solving the complicated large-scale combination optimization prob-lems ,GAs usually tend to converge prematurely because of the insufficient diversity of individuals.Diversity Enhancing Genetic Algorithm(DEGA)is presented to prevent premature convergence of GA,which introduced the ideas of affinity from immune system and cataclysm from biologic evolution process.DEGA searches all over the solution space as far as possible by lowering the affinities among the individuals of the initial population.Cataclysm is adopted to explore other better solu-tions than the local optimization in the solution space when the evolution process is halted,by which individuals are generated randomly again besides the best chromosome at present .As the proposed algorithm enhances the diversity of individuals in the solution space with a small size population well,it has a good global convergence performance and faster convergence speed.It has been successfully applied to optimal reactive power and voltage control of power systems.
【CateGory Index】: TM761.1
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