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《Automation of Electric Power Systems》 2002-23
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CATACLYSMIC GENETIC ALGORITHMS BASED OPTIMAL REACTIVE POWER PLANNING

Zhang Yongjun 1, Ren Zhen 1, Zhong Hongmei 1, Tang Zhuoyao 2, Shang Chun 2 (1. South China University of Technology, Guangzhou 510640, China)(2. Foshan Electric Power Bureau, Foshan 518000, China)  
This paper presents a Cataclysmic Genetic Algorithm for optimal reactive power planning of power systems. "Cataclysm" is introduced to ensure the diversities of the solution spaces; Grouping integer encoding technique and tournament selection method are adopted in this paper; Adjacent mutation operator integrating with integer encoding strategy is presented to avoid the Hamming cliffs by binary encoding strategy. The proposed algorithm applied to optimal reactive power planning on Foshan 226 bus power system. The results show that it is able to overcome the premature convergence tendency and to improve the local search performance of GA. It can be concluded that Cataclysmic Genetic Algorithm is much more efficient than traditional GA.
【CateGory Index】: TM715
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