Regionalized fault line in distribution networks based on an improved SSA-VMD and multi-scale fuzzy entropy

被引:4
作者
Chen, Bofan [1 ]
Sun, Yanzhou [1 ]
Song, Xiaoyan [2 ]
Wang, Bin [1 ]
机构
[1] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454000, Peoples R China
[2] Henan Elect Power Co, Elect Power Res Inst, Zhengzhou 450052, Peoples R China
基金
中国国家自然科学基金;
关键词
Fault line selection; Elite opposition-based learning strategy; Sparrow search algorithm; Variational modal decomposition; Multi-scale fuzzy entropy; ALGORITHM;
D O I
10.1007/s00202-023-01927-y
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To solve the insufficient utilization of transient power frequency current components when single-phase grounding fault occurs in high-voltage grounding system, a ground fault routing method based on improved sparrow search algorithm optimized variational modal decomposition (ISSA-VMD) and multi-scale fuzzy entropy (MFE) is proposed. First, the elite opposition-based learning strategy (EOBLS) is used to improve the population diversity of the SSA and adopt the improved SSA to optimize VMD's parameters. From the experimental data, we can know the optimized variational mode decomposition can accurately distinguish the power frequency components of each feeder transient zero-sequence current. Second, calculate the MFE value of the power frequency component of the zero-sequence current of each feeder and select the multi-scale fuzzy entropy partial mean (PMMFE) as the line selection criterion, and then, the fault line is selected. MATLAB/Simulink simulation experimental results and the experimental results of a real experimental field for a 10-kV distribution network show that this proposed method can select the right line under most mistake conditions, with high reliability and strong robustness.
引用
收藏
页码:4399 / 4408
页数:10
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