改进遗传算法在含DG配电网故障定位中的应用
DOI:
作者:
作者单位:

作者简介:

通讯作者:

基金项目:


Application of Improved Genetic Algorithms to Distribution Network Fault Location with DG
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    大量分布式电源接入配电网使其结构复杂多变,导致标准遗传算法故障定位效率和准确性受到影响。根据配电网运行的实际情况搭建故障定位数学模型,对标准遗传算法的开关函数和评价函数进行改进,提高了算法的容错性和准确性;引入配电网分级处理的概念,对配电网进行分区处理,将整个配电网分为若干个独立区域,缩短了算法中解的维度,从而提高算法定位的效率;最后通过MATLAB对不同故障类型算例进行仿真,结果表明改进后的遗传算法在含分布式电源的配电网中有很好的容错能力,通过对其仿真时间和精准度进行分析,结果表明算法运算效率和准确性都很高。

    Abstract:

    A large number of distributed generations are connected to the distribution network, which makes its structure complex and changeable, resulting in the impact on the efficiency and accuracy of fault location of standard genetic algorithm.According to the actual situation of distribution network operation, a fault location mathematical model is built, and the switch function and evaluation function of standard genetic algorithm are improved, which improves the fault tolerance and accuracy of the algorithm.At the same time, the concept of hierarchical processing of distribution network is introduced to partition the distribution network, dividing the whole distribution network into several independent regions, which shortens the dimension of solution in the algorithm and improves the efficiency of algorithm location.Finally, different fault types are simulated by MATLAB.The results show that the improved genetic algorithm has good faulttolerant ability in the distribution network with distributed generators.The simulation time and accuracy are analyzed.The results show that the algorithm has high operational efficiency and accuracy.

    参考文献
    相似文献
    引证文献
引用本文

郭保健, 卞显新.改进遗传算法在含DG配电网故障定位中的应用[J].重庆工商大学学报(自然科学版),2019,36(5):24-30
GUO Bao-jian, BIAN Xian-xin. Application of Improved Genetic Algorithms to Distribution Network Fault Location with DG[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2019,36(5):24-30

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2019-10-09
×
2023年《重庆工商大学学报(自然科学版)》影响因子稳步提升