河北大学学报(自然科学版) ›› 2020, Vol. 40 ›› Issue (1): 87-94.DOI: 10.3969/j.issn.1000-1565.2020.01.013

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递归搜索与遗传算法融合的终端优化配置方法

张强1,杨云杰1,赵妙1,霍利民1,唐巍2   

  • 收稿日期:2019-03-27 出版日期:2020-01-25 发布日期:2020-01-25
  • 通讯作者: 霍利民(1965—),男,河北安国人,河北农业大学教授,博士生导师,主要从事农业电气化与自动化研究.E-mail: huolimin@126.com
  • 作者简介:张强(1994—),男,河北唐山人,河北农业大学在读硕士研究生. E-mail:848560563@qq.com
  • 基金资助:
    国家自然科学基金资助项目(51377162)

Optimal terminal configuration method based on recursive search and genetic algorithms

ZHANG Qiang1,YANG Yunjie1,ZHAO Miao1,HUO Limin1,TANG Wei2   

  1. 1.College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071000, China; 2.School of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
  • Received:2019-03-27 Online:2020-01-25 Published:2020-01-25

摘要: 提出了基于递归搜索与遗传算法融合的终端配置优化方法,该方法以各负荷点为起点在含有配电终端的配电网进行主回路搜索和子回路搜索,搜索同时依次判断当前故障对负荷节点的供电可靠性的影响并累加停电时间.通过构建选择算子的选择条件,将递归搜索可靠性计算方法与遗传算法深度结合,能够快速求解配电终端优化问题,易于在计算机上编程实现,且能够在只修改网络基本参数的前提下,得出不同配电网的终端配置的最优方案.算例以不同的平均供电可用率指标作为约束,分析不同约束下的终端配置方案和经济效益,验证了所提算法的有效性.

关键词: 可靠性, 终端优化, 递归搜索, 遗传算法

Abstract: A terminal configuration optimization method based on the combination of depth-first search and genetic algorithm is proposed. This method uses each load point as the starting point to search the main circuit and sub-circuit in the distribution network with distribution terminals. The search simultaneously judges the influence of current faults on the reliability of power supply at load points and accumulates. By constructing the selection conditions of selection operators, the depth-first search can be carried out. The combination of reliability calculation method and genetic algorithm can solve the optimization problem of distribution terminals quickly, and can be easily programmed on computer. It can also solve the optimal terminal configuration of different distribution networks on the premise of modifying only the basic parameters of the network. The calculation example takes different average power supply availability as constraints, and analyses the terminal configuration scheme and economic benefits under different constraints, which verifies the effectiveness of the proposed algorithm.

Key words: reliability, terminal optimization, recursively searching, genetic algorithms

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