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《Power System Technology》 2004-11
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MULTIPLE-OBJECTIVE REACTIVE POWER OPTIMIZATION BASED ON IMPROVED GENETIC ALGORITHM

ZHANG Wu-jun;YE Jian-feng;LIANG Wei-jie;FANG Ge-fei School of Electrical Engineerng, Zhejiang University, Hangzhou 310027, Zhejiang Province, China  
A modified genetic algorithm for reactive power optimization is presented. On the basis of the existing improved genetic algorithm, it is pointed out that to ensure the population diversity and to speed up the convergence the penalty coefficient with linear and exponential variation laws is applied to the objective function containing multi-objects, and the sufficiency function is modified by simulated annealing. Using the adaptive variance of the genetic factor and the improved variation operation, the global and partial optimization ability can be obviously improved. The results of calculation and simulation for IEEE 14-bus system show that in the aspects of calculation speed and convergence ability the presented method is better than simple genetic algorithm, and the convergence speed will be faster when the penalty coefficient varies by exponential law rather than the constant or linear variation law.
【CateGory Index】: TM714
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