基于VMD的小电流接地故障融合选线方法

孙孔明; 李玉敦; 范荣奇; 薛永端; 庞清乐; 徐宪泽

doi:10.13272/j.issn.1671-251x.2022080082

基于VMD的小电流接地故障融合选线方法

doi: 10.13272/j.issn.1671-251x.2022080082

1.
国网山东省电力公司电力科学研究院, 山东济南　250003
2.
国网山东省电力公司, 山东济南　250001
3.
中国石油大学(华东) 新能源学院, 山东青岛　266580

基金项目: 国网山东省电力公司科技项目(5206002000TZ)。

详细信息

作者简介:
孙孔明（1989—），男，山东潍坊人，博士，主要从事继电保护技术、配电网优化与控制工作，E-mail: skming2008@163.com

中图分类号: TD608
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出版历程
- 收稿日期: 2022-08-29
- 修回日期: 2023-03-02
- 网络出版日期: 2022-10-21

Fusion fault line selection method of small current grounding fault based on VMD

1.
State Grid Shandong Electric Power Research Institute, Jinan 250003, China
2.
State Grid Shandong Electric Power Company, Jinan 250001, China
3.
College of New Energy, China University of Petroleum(East China), Qingdao 266580, China

摘要

摘要: 针对目前煤矿配电网故障选线方法在相关故障特征不明显时存在故障选线失效，基于单一模态分量和单一故障特征的故障选线方法的选线准确度较低等问题，提出了一种基于变分模态分解（VMD）的小电流接地故障融合选线方法。利用VMD将母线中各出线的故障零序电流分解为多个模态分量，根据模态分量的故障特征确定VMD层数，并选取故障特征明显的模态分量作为故障选线的有效模态分量；分别计算各出线故障零序电流有效模态分量的暂态能量和波形相似度；根据各出线有效模态分量的暂态能量占比和波形相似度占比，构建基于暂态能量的故障选线判据和基于波形相似度的故障选线判据，并将2种故障选线判据融合，形成基于VMD的故障融合选线算法。利用电磁暂态仿真软件ATP/EMTP搭建煤矿配电网模型，在不同接地故障电阻、故障初相角和故障位置的单相接地故障场景下，对所提出的故障融合选线方法进行验证，结果表明：在配电网发生各种单相接地故障时，基于VMD的小电流接地故障融合选线方法不受故障位置的影响，较能量法和相关性聚类法的故障选线正确率分别提高了17%和50%，且不受故障类型影响，可应用于小电流接地故障选线。
- 煤矿配电网 /
- 小电流接地系统 /
- 故障融合选线 /
- 变分模态分解 /
- 高频振荡分量 /
- 模态分量 /
- 暂态能量 /
- 波形相似度
Abstract: At present, the fault line selection method of coal mine distribution network has the problem of fault line selection failure when the relevant fault features are not obvious. The fault line selection method based on single modal component and single fault feature has low accuracy. In order to solve the above problems, a method of small current grounding fusion fault line selection based on variational mode decomposition (VMD) is proposed. VMD is used to decompose the fault zero-sequence current of each outgoing line in the bus into multiple modal components. The layer number of the VMD is determined according to the fault features of the modal components. The modal components with obvious fault features are selected as effective modal components for fault line selection. The transient energy and the waveform similarity of the effective modal component of the zero sequence current of each outgoing line fault are calculated respectively. According to the proportion of transient energy and the proportion of waveform similarity of effective modal components of each outgoing line, a fault line selection criterion based on transient energy and a fault line selection criterion based on waveform similarity are constructed. The two fault line selection criteria are fused to form a fault fusion line selection algorithm based on VMD. A coal mine distribution network model is built by using the electromagnetic transient simulation software ATP/EMTP. The proposed fusion fault line selection method is verified under single-phase-to-ground fault scenarios with different ground fault resistances, fault initial phase angles and fault locations. The results show that when various single-phase ground faults occur in the distribution network, the fusion line selection method of small-current grounding fault based on VMD is not affected by the fault location. The fault line selection accuracy is respectively improved by 17% and 50% compared with the energy method and the correlation clustering method. The fusion line selection method is not affected by the fault type, and can be applied to the small current grounding fault line selection.
- coal mine distribution network /
- small current grounding system /
- fusion fault line selection /
- variational mode decomposition /
- high-frequency oscillation component /
- modal component /
- transient energy /
- waveform similarity

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图 1 单相接地故障零序等效电路

Figure 1. Zero sequence equivalent circuit of single-phase ground fault

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图 2 煤矿配电网模型

Figure 2. Coal mine distribution network model

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图 3 不同模态分量个数下的VMD结果

Figure 3. Variational pecomposition (VMD) decomposition results under different mode component number

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图 4 高阻接地故障时VMD结果

Figure 4. VMD decomposition results in case of high resistance grounding fault

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图 5 故障融合选线流程

Figure 5. Fault fusion line selection process

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表 1 提取IMF₂分量时的故障选线数据

Table 1. Fault line selection data when extracting IMF₂ component

R_g /Ω	φ /（°）	S₂		S₃		S₄		故障线路
R_g /Ω	φ /（°）	Δ₂₂	η₂₂	Δ₂₃	η₂₃	Δ₂₄	η₂₄	故障线路
0.5	0	0.110 6	0.999 8	0.105 6	0.999 8	0.783 8	−0.999 7	S₄
	45	0.113 2	1.064 1	0.114 1	1.064 1	0.772 6	−1.128 2	S₄
	90	0.110 2	1.058 0	0.116 2	1.058 0	0.773 6	−1.115 9	S₄
10	0	0.000 5	0.504 4	0.000 5	0.504 4	0.999 0	−0.008 8	S₄
	45	0.150 2	1.571 6	0.132 3	1.571 6	0.717 5	−2.143 2	S₄
	90	0.151 3	1.438 5	0.133 9	1.438 5	0.714 8	−1.876 9	S₄
1 000	0	0.004 6	0.499 3	0.003 8	0.499 3	0.991 5	0.001 4	S₄
	45	0.000 5	−1.00 71	0.000 0	0.003 5	0.999 5	0.003 5	S₄
	90	0.002 4	0.094 3	0.000 2	0.452 8	0.997 4	0.452 8	无
2 000	0	0.004 7	0.498 0	0.003 9	0.498 0	0.991 4	0.004 0	S₄
	45	0.000 4	−1.002 3	0.000 0	0.001 1	0.999 5	0.001 1	S₄
	90	0.002 2	0.099 0	0.000 2	0.450 5	0.997 6	0.450 5	无

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表 2 提取IMF₃分量时的故障选线数据

Table 2. Fault line selection data when extracting IMF₃ component

R_g /Ω	φ/（°）	S₂		S₃		S₄		故障线路
R_g /Ω	φ/（°）	Δ₃₂	η₃₂	Δ₃₃	η₃₃	Δ₃₄	η₃₄	故障线路
1 000	90	0.147 4	1.222 6	0.104 5	1.222 6	0.748 1	−1.445 2	S₄
2 000	90	0.145 8	1.183 7	0.103 7	1.183 7	0.750 5	−1.367 3	S₄

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表 3 不同故障位置的故障选线数据

Table 3. Fault line selection data at different fault locations

故障位置	S₂		S₃		S₄		故障线路
故障位置	Δ₃₂	η₃₂	Δ₃₃	η₃₃	Δ₃₄	η₃₄	故障线路
f₁	0.313 9	0.020 7	0.060 6	0.020 7	0.625 4	−1.041 4	S₄
f₂	0.132 6	1.065 9	0.067 0	1.065 9	0.800 4	−1.131 8	S₇
f₃	0.143 4	0.998 4	0.067 6	0.998 4	0.789 0	−0.996 9	S₁₀

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表 4 不同故障选线方法的选线结果

Table 4. Line selection results of different fault line selection methods

R_g /Ω	φ/(°)	能量法		相关性聚类法		融合选线法
R_g /Ω	φ/(°)	故障线路	选线结果	故障线路	选线结果	故障线路	选线结果
0.5	0	S₄	正确	S₄	正确	S₄	正确
	45	S₄	正确	S₄	正确	S₄	正确
	90	S₄	正确	S₄	正确	S₄	正确
10	0	S₄	正确	S₄	正确	S₄	正确
	45	母线	错误	S₄	正确	S₄	正确
	90	母线	错误	S₄	正确	S₄	正确
1 000	0	S₄	正确	母线	错误	S₄	正确
	45	S₄	正确	S₂	错误	S₄	正确
	90	S₄	正确	母线	错误	S₄	正确
2 000	0	S₄	正确	母线	错误	S₄	正确
	45	S₄	正确	S₂	错误	S₄	正确
	90	S₄	正确	母线	错误	S₄	正确

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