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Based on the genetic algorithm and the improved model for Substation Locating and Sizing
Author(s): 
Pages: 3048-3050
Year: Issue:  z1
Journal: East China Electric Power

Keyword:  power system planningsubstation locating and sizinggenetic algorithmGADS toolbox;
Abstract: 给出了变电站成本与负荷需求相结合的寻求最优寻址的投资策略的新目标函数,并且采用了Matlab 中的遗传算法工具箱GADS(Toolboxes-Genetic Algorithm and Direct Search)运行实现,最终通过结合投资成本与连接方式得到了最优变电站数量与变电站寻址结果的最佳配置,同时针对110 kV电力网络规划中变电站选址定容的结构复杂,变量多的特点,利用遗传算法(Genetic Algorithm)概率化的寻优方法,自动获取和指导优化的搜索空间,自适应地调整搜索方向的特性进行寻址操作,并通过实例计算验证了其合理性、科学性.
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