Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation

doi:10.11930/j.issn.1004-9649.202307049

Abstract

Abstract:

In the state estimation of distribution systems, it is difficult to fully monitor numerous network devices, resulting in insufficient measurement data. Besides, frequent topology switching urgently requires efficient algorithms. Therefore, this paper proposed an effective weighted minimum absolute value state estimation method for distribution network topology identification. Firstly, the traditional weighted minimum absolute value state estimation method based on linear programming was improved to improve the calculation efficiency. Secondly, a weighted minimum absolute value state estimation method based on mixed integer linear programming was formed by adding supplementary variables and constraints to the reformulated weighted minimum absolute value state estimation method to adapt to the topology identification problem. The simulation results on four example systems validate the excellent performance of the proposed topology identification method in different amounts of real-time measurements, high pseudo measurement errors, measurements corrupted by bad data, and unknown branch state scenarios.

Key words: distribution system, state estimation, topology identification, weighted minimum absolute value, mixed integer linear programming

Guang MA, Wen ZHU, Huijie GU, Huashi ZHAO, Xiqi HE, Shijie CHEN. Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation[J]. Electric Power, 2024, 57(1): 167-174.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202307049

https://www.electricpower.com.cn/EN/Y2024/V57/I1/167

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References 26

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系统	状态估计方法	平均迭代次数	平均求解时间/s	E_MAP/%
33节点	本文	3.10	17.56	0.51
33节点	传统	3.10	29.87	0.49
69节点	本文	3.20	22.27	0.42
69节点	传统	3.10	42.27	0.40
123节点	本文	3.16	25.27	0.49
123节点	传统	3.01	71.19	0.48
417节点	本文	3.10	174.64	0.46
417节点	传统	3.10	1956.12	0.46

系统	状态估计方法	平均迭代次数	平均求解时间/s	E_MAP/%
33节点	本文	3.10	17.56	0.51
33节点	传统	3.10	29.87	0.49
69节点	本文	3.20	22.27	0.42
69节点	传统	3.10	42.27	0.40
123节点	本文	3.16	25.27	0.49
123节点	传统	3.01	71.19	0.48
417节点	本文	3.10	174.64	0.46
417节点	传统	3.10	1956.12	0.46

测量类型		位置（节点/支路）	误差/%
实时测量	电压幅值	任意	1
实时测量	潮流	任意	3
伪测量	注入功率	所有负荷节点	50
虚拟测量	注入功率	28, 39, 57, 92, 104	–
虚拟测量	参考角	1	–

测量类型		位置（节点/支路）	误差/%
实时测量	电压幅值	任意	1
实时测量	潮流	任意	3
伪测量	注入功率	所有负荷节点	50
虚拟测量	注入功率	28, 39, 57, 92, 104	–
虚拟测量	参考角	1	–

α_rt /%	方法	A/%	E_MAP/%	平均求解时间/s
80	本文	100	0.04	9.20
80	文献[14]	45	0.06	55.84
70	本文	94	0.05	13.77
70	文献[14]	37	0.20	55.48
60	本文	98	0.05	14.14
60	文献[14]	55	0.10	61.34
50	本文	100	0.05	16.26
50	文献[14]	33	0.12	90.21
40	本文	93	0.07	78.21
40	文献[14]	24	0.10	104.56