注入电流分布特性辨识的配电网故障选线方法

doi:10.11930/j.issn.1004-9649.202401043

中国电力 ›› 2024, Vol. 57 ›› Issue (10): 78-89.DOI: 10.11930/j.issn.1004-9649.202401043

• 新型配电系统保护与控制关键技术 • 上一篇下一篇

注入电流分布特性辨识的配电网故障选线方法

王晓卫¹(), 岳阳¹(), 郭亮²(), 王雪¹, 王毅钊³, 张志华³, 杨峰峰⁴

1. 西安理工大学电气工程学院，陕西西安　710054
2. 国网江西省电力有限公司电力科学研究院，江西南昌　330000
3. 国网陕西省电力有限公司电力科学研究院，陕西西安　710100
4. 浙江省送变电工程有限公司，浙江杭州　310020

收稿日期:2024-01-09 出版日期:2024-10-28 发布日期:2024-10-25
作者简介:王晓卫（1983—），男，通信作者，博士，副教授，从事电力系统继电保护、配电网接地故障处理研究，E-mail：proceedings@126.com
岳阳（1995—），男，硕士研究生，从事电力系统继电保护研究，E-mail：yue4230@126.com
郭亮（1986—），男，硕士，高级工程师，从事配电网继电保护研究，E-mail：guoliangxinyu@126.com
基金资助:
国家自然科学基金资助项目（52177114）。

Injection Current Distribution Characteristics Identification Based Distribution-Level Fault Line Selection

Xiaowei WANG¹(), Yang YUE¹(), Liang GUO²(), Xue WANG¹, Yizhao WANG³, Zhihua ZHANG³, Fengfeng YANG⁴

1. School of Electrical Engineering, Xi'an University of Technology, Xi'an 710054, China
2. Institute of Electric Power Research of Jiangxi Electric Power Company, Nanchang 330000, China
3. Institute of Electric Power Research of Shaanxi Electric Power Company, Xi'an 710100, China
4. Zhejiang Electric Transmission & Transformation Co., Ltd., Hangzhou 310020, China

Received:2024-01-09 Online:2024-10-28 Published:2024-10-25
Supported by:
This work is supported by National Natural Science Foundation of China (No.52177114).

摘要/Abstract

摘要：

针对谐振接地系统单相接地故障特征微弱，基于故障特征的选线方法灵敏度和可靠性降低的问题，提出一种主动注入信号辨识的故障选线方法。首先，推导了注入电流受线路对地导纳影响下的分布特性，利用此分布特性构造选线判据。然后，从不同角度分析了注入信号对系统运行的影响，选择适宜参数的注入信号。考虑降低注入频率能够提高主动注入式选线方法的耐过渡电阻能力，故选择注入低频信号。测量注入信号后各条馈线的零序电流，选择稳态零序电流时间窗，利用Prony算法辨识各条线路零序电流中25 Hz电流幅值完成故障选线。最后，Pscad仿真和现场实测波形验证结果表明，该方法在不同故障场景下均能准确实现故障选线，且具有良好的耐过渡电阻能力。

关键词: 配电网, 单相接地故障, 注入法, Prony算法辨识, 故障选线

Abstract:

Addressing the challenges posed by the subtle characteristics of single-phase grounding faults in resonant grounding systems, which lead to decreased sensitivity and reliability in fault line selection methods reliant on these characteristics, an innovative approach for fault line selection through active injection signal identification is proposed. Initially, the distribution characteristics of the injected current, influenced by line-to-ground conductance, are derived. These characteristics then form the foundation for constructing a robust line selection criterion. Furthermore, a thorough analysis is conducted to assess the impact of the injected signal on system operation from various perspectives. This analysis leads to the selection of an optimal injection signal with suitable parameters. Notably, to enhance the method's resilience against transition resistance, a decision is made to inject a low-frequency signal. Subsequently, the zero-sequence current of each feeder line is measured after injecting the signal. A specific steady-state zero-sequence current time window is identified, and the Prony algorithm is employed to accurately discern the 25Hz current amplitude within the zero-sequence current of each line. This approach enables precise fault line selection. Extensive PSCAD simulations and on-site waveform measurements validate the effectiveness of this method. The results demonstrate its ability to accurately identify fault lines across a range of fault scenarios, while maintaining excellent resistance to transition resistance.

Key words: distribution network, single phase ground fault, injection method, Prony algorithm identification, fault line selection

王晓卫, 岳阳, 郭亮, 王雪, 王毅钊, 张志华, 杨峰峰. 注入电流分布特性辨识的配电网故障选线方法[J]. 中国电力, 2024, 57(10): 78-89.

Xiaowei WANG, Yang YUE, Liang GUO, Xue WANG, Yizhao WANG, Zhihua ZHANG, Fengfeng YANG. Injection Current Distribution Characteristics Identification Based Distribution-Level Fault Line Selection[J]. Electric Power, 2024, 57(10): 78-89.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202401043

https://www.electricpower.com.cn/CN/Y2024/V57/I10/78

图/表 16

图 1 含多馈线配网的等效运算电路

Fig.1 Equivalent arithmetic circuits of distribution networks with multiple feeders

图 2 零序电流注入后单相接地等效电路

Fig.2 Equivalent circuit of single-phase grounding after zero sequence current injection

图 3 注入信号辨识选线方法流程

Fig.3 Injection signal identification flow

图 4 注入式故障选线多馈线系统

Fig.4 Schematic diagram of injection fault line selection for multi feeder system

表 1 线路参数

Table 1 Line parameters

线路类型	相序	电阻/(Ω·km^–1)	电感/(mH·km^–1)	电容/(uF·km^–1)
架空线路	零序	0.2300	5.4800	0.0060
架空线路	正序	0.1700	1.2000	0.0097
电缆线路	零序	2.7000	1.0190	0.2800
电缆线路	正序	0.2700	0.2550	0.3390

图 5 故障线路零序电流时间窗

Fig.5 Fault line zero sequence current time window

图 6 健全线路零序电流时间窗

Fig.6 Zero sequence current time window of healthy line

表 2 选线结果

Table 2 Line selection results

故障点	接地电阻/Ω	L₁/ 10^–3	L₂/ 10^–3	L₃/ 10^–3	L₄/ 10^–3	L₅/ 10^–3	选线结果
f₁	50	3.40	0.02	0.23	0.11	0.36	L₁
	200	1.40	0.03	0.32	0.15	0.45	L₁
	500	0.66	0.03	0.33	0.15	0.43	L₁
f₂	50	0.27	3.50	0.23	0.11	0.35	L₂
	200	0.36	1.30	0.32	0.15	0.45	L₂
	500	0.35	0.55	0.33	0.15	0.43	L₂
f₃	50	0.29	0.02	3.30	0.12	0.38	L₃
	200	0.36	0.03	1.30	0.15	0.45	L₃
	500	0.35	0.03	0.63	0.15	0.43	L₃
f₄	50	0.27	0.02	0.23	3.40	0.36	L₄
	200	0.36	0.03	0.32	1.30	0.45	L₄
	500	0.36	0.03	0.32	0.57	0.43	L₄
f₅	50	0.28	0.02	0.24	0.11	3.40	L₅
	200	0.36	0.03	0.32	0.15	1.40	L₅
	500	0.35	0.03	0.33	0.15	0.73	L₅

图 7 实测零序电流波形及数据窗选取

Fig.7 Measured zero sequence current and data window

图 8 注入后零序电流波形

Fig.8 Zero sequence current waveform after injecting

图 9 滤波后的电流波形

Fig.9 Current waveform after filtering

图 10 Prony拟合效果

Fig.10 Schematic diagram of Prony fitting effect

表 3 实测波形辨识结果

Table 3 Identification results of measured waveforms

线路	注入低频信号幅值/A	辨识结果/A
915	2.8	3.1
913	4.3	4.7
937	1.3	1.8
929	8.5	9.8
927	12.4	31.0

图 11 实测零序电流及数据窗选取

Fig.11 Measured zero sequence current and data window

图 12 注入后零序电流波形

Fig.12 Zero sequence current waveform after injecting

表 4 实测波形辨识结果

Table 4 Identification results of measured waveforms

线路	注入低频信号幅值/A	辨识结果/A
通道9	3.8	4.2
通道10	4.3	5.4
通道11	3.9	6.8
通道12	0.3	1.2
通道14	16.8	14.0

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注入电流分布特性辨识的配电网故障选线方法

Injection Current Distribution Characteristics Identification Based Distribution-Level Fault Line Selection

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注入电流分布特性辨识的配电网故障选线方法

Injection Current Distribution Characteristics Identification Based Distribution-Level Fault Line Selection

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