摘要
根据电力系统无功优化问题的特点,提出了一种基于近似最优个体、学习算子和浑沌算子的改进遗传算法。传统遗传算法应用于电力系统无功优化问题,虽然收到了比较好的效果,但并没有充分利用电力系统本身的特点。而本研究所提的改进遗传算法,可以充分利用已有的信息和运行经验,从而达到在保证解的全局最优性的同时大大加快计算的速度。具体的算例表明了所提算法的正确性和有效性。
An improved genetic algorithm based on ＂approximative elite＂, ＂study operator＂ and ＂chaos operator＂ has been presented in this paper according to the features of reactive power optimization in power system. The calculational efficiency can been improved obviously as well as the best solution can be kept assuredly if the improved genetic algorithm presented in this paper is used because of the consideration of the existed information and operation experience, which are not considered carefully in traditional genetic algorithm, thought some good effect has been got by the traditional genetic algorithm in solving this problem. A numerical example shows the correctness and validity of the algorithm presented in this paper.
关键词
遗传算法
学习算子
混沌操作
电力系统
无功优化
genetic algorithm
study operator
chaos operator
power system
reactive power optimization
