邹长青, 刘对, 林兵, 卢宇, 刘洁彤. 基于特征能量和BFAGA算法的含分布式电源配电网单相接地故障区段定位[J]. 高电压技术, 2024, 50(6): 2706-2715. DOI: 10.13336/j.1003-6520.hve.20221537
引用本文: 邹长青, 刘对, 林兵, 卢宇, 刘洁彤. 基于特征能量和BFAGA算法的含分布式电源配电网单相接地故障区段定位[J]. 高电压技术, 2024, 50(6): 2706-2715. DOI: 10.13336/j.1003-6520.hve.20221537
ZOU Changqing, LIU Dui, LIN Bing, LU Yu, LIU Jietong. Single-phase Ground Fault Location of Distribution Network with Distributed Generator Based on Characteristic Energy and BFAGA Algorithm[J]. High Voltage Engineering, 2024, 50(6): 2706-2715. DOI: 10.13336/j.1003-6520.hve.20221537
Citation: ZOU Changqing, LIU Dui, LIN Bing, LU Yu, LIU Jietong. Single-phase Ground Fault Location of Distribution Network with Distributed Generator Based on Characteristic Energy and BFAGA Algorithm[J]. High Voltage Engineering, 2024, 50(6): 2706-2715. DOI: 10.13336/j.1003-6520.hve.20221537

基于特征能量和BFAGA算法的含分布式电源配电网单相接地故障区段定位

Single-phase Ground Fault Location of Distribution Network with Distributed Generator Based on Characteristic Energy and BFAGA Algorithm

  • 摘要: 含分布式电源的线-缆混合新型配电网发生单相接地故障时,故障位置采用传统区段定位方法难以准确定位。对此,提出了基于特征能量和二进制萤火虫遗传算法的方法,对新型配电网进行故障区段定位。首先,通过集合经验模态分解求取特征频段内配电网各馈线首端零序电流分量能量之和,判定故障线路进行故障选线;其次,在实现选线的基础上,根据故障区段两端零序电流幅值与健全区段零序电流幅值存在较大差别的特点,采用相关系数法对开关进行实际编码;最后,通过二进制萤火虫遗传算法求得适应度函数最优解,进而得到故障区段。仿真分析以及算法性能对比结果表明,所提方法求解速度更快,准确性更高,具有一定的容错性。

     

    Abstract: When single-phase grounding fault occurs in a new type of wire-cable hybrid distribution network with distributed generator, it is difficult to locate the fault accurately by using the traditional section locating method. In this paper, a method based on characteristic energy and binary firefly genetic algorithm is proposed to locate fault segments in the new distribution network. Firstly, the sum of the zero-sequence current components at the head end of each feeder in the characteristic frequency band was obtained by ensemble empirical mode decomposition, and the fault line was determined for fault line selection. Secondly, based on the realization of line selection, the correlation coefficient method is used to code the switch according to the great difference between the zero-sequence current amplitude at both ends of the fault section and the zero-sequence current amplitude in the healthy section. Finally, the optimal solution of fitness function is obtained by binary firefly genetic algorithm. Simulation analysis and algorithm performance comparison show that the proposed method is faster, more accurate and has certain fault tolerance.

     

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