Accurate Location Method for Abnormal Line Losses in Distribution Network Considering Topology Matching and Parameter Estimation in Grid

Haiyun An, Qian Zhou, Qiuwei Wu, Yufang Liu, Cheng Huang and Jiaxun Li ()
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Haiyun An: State Grid Jiangsu Electric Power Research Institute, Nanjing 211100, China
Qian Zhou: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
Qiuwei Wu: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
Yufang Liu: State Grid Jiangsu Electric Power Research Institute, Nanjing 211100, China
Cheng Huang: State Grid Jiangsu Electric Power Research Institute, Nanjing 211100, China
Jiaxun Li: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

Energies, 2025, vol. 18, issue 9, 1-12

Abstract: With the increasing emphasis on managing line losses, accurately locating and analyzing abnormal line losses in distribution networks has become a critical challenge in implementing effective loss reduction strategies. Aiming at locating and analyzing abnormal line losses caused by equipment aging in the distribution network, an accurate location method considering topology matching and parameter estimation in the grid is proposed. Firstly, a topology matching model based on a support vector machine in the grid is established to identify the real-time topology connection relationship within the distribution network. The accuracy of SVM is enhanced through an optimized parameter selection strategy. Secondly, a multi-objective optimization model is built employing the operation data collected by the measurement equipment, focusing on voltage and power estimation to form a parameter estimation model. This model focuses on voltage and power estimation, improving the accuracy of parameter estimation compared to single-parameter optimization methods. The weighting coefficient is selected to minimize the solution error. Finally, by comparing the deviation between the estimated values of the branch parameters and the theoretical values, the aging degree of each branch is evaluated, and branches with abnormal line losses are accurately located. The effectiveness of the proposed method is verified using the IEEE 33-bus distribution network, demonstrating its potential for improving the accuracy of identifying abnormal line losses caused by equipment aging and supporting enhanced distribution network management.

Keywords: abnormal line losses; topology matching; parameter estimation; equipment aging (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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