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无功优化控制是保证电能经济传输与经济运行的重要条件,在满足电力系统各种运行约束条件下,通过优化计算来确定控制变量,找到使系统的一个或多个性能指标达到最优时的无功调节补偿手段。遗传算法用于电力系统无功优化,具有简单通用、鲁棒性强和可并行计算等优点。对简单遗传算法在罚函数、选择、变异、交叉和终止条件等方面进行一些改进,可以加快遗传算法的收敛速度,使结果趋于更优,实际算例也证明了这一点。
Reactive power optimization control is an important condition to ensure economic transmission and economic operation of power system. When various operational constraints of the power system are met, the control variables are determined through optimization calculation, and when one or more performance indexes of the system are found to be optimal Reactive power compensation method. Genetic algorithm is used for power system reactive power optimization, with the advantages of simple and universal, strong robustness and parallel computing. Some improvements to the simple genetic algorithm in the penalty function, selection, mutation, crossover and termination conditions, can speed up the convergence of genetic algorithm, the result tends to be better, the actual example also proved this point.