摘要
为了解决舰船电力系统故障恢复的问题,根据故障恢复快速性的要求提出了一种新的混沌遗传算法,尝试改进遗传算法,采用遗传算法代替混沌优化算法中的"细搜索";同时用混沌优化算法中的"粗搜索"来初始化遗传算法的种群,以保证初始种群含有较丰富的模式,从而增加搜索快速收敛于全局最优解的可能。对典型的模型仿真结果表明,该算法具有更好的收敛性能,有效提高了故障恢复的速度和精度,避免了陷入局部最优的可能。
To deal with problems of shipboard power system service restoration, the paper presents a new chaos genetic algorithm according to the service restoration＇s request of speediness. The paper improves genetic arithmetic, uses genetic algorithm to replace ＂thin search＂ in the chaos optimization, and uses ＂thick search＂ in the chaos optimization to initialize the population of the genetic algorithm, which assures the population diversity and avoids get to stuck in local minima, Typical SPS service restoration tests show that the chaos genetic algorithm can improve speed of convergence and precision of restoration and avoid premature convergence.
出处
《继电器》
CSCD
北大核心
2007年第21期39-42,共4页
Relay
基金
海军装备部预研项目(A3820061202)
江苏省高校自然科学基金项目(06KJB510030)
关键词
混沌
遗传算法
舰船电力系统
故障恢复
chaos
genetic algorithm
shipboard power system
service restoration
