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《Power System Technology》 2008-12
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A Reactive Power Optimization Method Based on Improved Quantum-Inspired Genetic Algorithm

LIU Hong-wen,ZHANG Ge-xiang (School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,Sichuan Province,China)  
A new improved quantum-inspired genetic algorithm(IQGA)based approach to optimize power system reactive power is proposed,in which several conception in quantum calculation are used for reference and the quantum bit is used in the coding of control variables,such coding mode can represent many possible linear superposition states,thus the population diversity can be maintained better.Meanwhile, the quantum gate is updated by the researched optimal individual information to quicken the convergence speed of this algorithm;besides,the population catastrophe strategy is adopted to prevent this algorithm fall into premature convergence.The reactive power optimization for IEEE 6-bus system and IEEE 30-bus system is performed by linear programming algorithm,Box algorithm,MTSA algorithm, standard genetic algorithm,adaptive genetic algorithm and the proposed algorithm respectively,optimization results show that the proposed algorithm possesses strong global searching capability and it can converge rapidly.
【Fund】: 国家自然科学基金资助项目(60702026)~~
【CateGory Index】: TP18;TM714
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