A Method for Small Current Grounding Fault Location Based on the Modified D-S Evidence Theory with Multi-Criteria Basic Belief Assignment Adjustment

In order to overcome the limitations and insufficient accuracy of the single identification method of small current grounding fault and enhance the applicability of the identification method, a method for small current grounding fault location based on the modified d-s evidence theory with multi-criteria basic belief assignment adjustment is proposed. Firstly, the duality and difference of fault characteristics of zero-sequence current and phase current after single-phase grounding fault are analyzed. Based on the three methods of transient zero-sequence reactive power direction, zero-sequence capacitance parameter identification and phase current mutation direction, the fault characteristics are binarized to construct the fusion sub-criterion. Then, the performance of each criterion is evaluated by using the historical discriminant confusion matrix and the check reliability factor of the two nearest neighbor discriminants. According to the positive judgment rate of each criterion, the basic belief assignment is dynamically modified in a data-driven manner to ensure that the high-accuracy criterion obtains higher basic belief assignment. Based on the D-S evidence theory, the multi-criteria information is fused to form a comprehensive criterion for small current grounding fault. Finally, the simulation model is constructed in DigSilent/PowerFactory, and the simulation waveforms under 1000 random fault scenarios are tested. The results show that the correct rate of the proposed method is 90.6 %, and it has a high correct rate in different fault scenarios, which is better than a single criterion, which verifies the effectiveness and superiority of the proposed method.

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Published
2024-10-25
DOI
https://doi.org/10.1109/icsgsc62639.2024.10813970
Primary Topic
Advanced Decision-Making Techniques
Type
article
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article

A Method for Small Current Grounding Fault Location Based on the Modified D-S Evidence Theory with Multi-Criteria Basic Belief Assignment Adjustment

Pengyu Qiu, Xiaojie Hei, Xin Qu, Jiangbo Wang
Advanced Decision-Making Techniques
article

A Method for Small Current Grounding Fault Location Based on the Modified D-S Evidence Theory with Multi-Criteria Basic Belief Assignment Adjustment

Pengyu Qiu, Xiaojie Hei, Xin Qu, Jiangbo Wang
article en

Abstract

In order to overcome the limitations and insufficient accuracy of the single identification method of small current grounding fault and enhance the applicability of the identification method, a method for small current grounding fault location based on the modified d-s evidence theory with multi-criteria basic belief assignment adjustment is proposed. Firstly, the duality and difference of fault characteristics of zero-sequence current and phase current after single-phase grounding fault are analyzed. Based on the three methods of transient zero-sequence reactive power direction, zero-sequence capacitance parameter identification and phase current mutation direction, the fault characteristics are binarized to construct the fusion sub-criterion. Then, the performance of each criterion is evaluated by using the historical discriminant confusion matrix and the check reliability factor of the two nearest neighbor discriminants. According to the positive judgment rate of each criterion, the basic belief assignment is dynamically modified in a data-driven manner to ensure that the high-accuracy criterion obtains higher basic belief assignment. Based on the D-S evidence theory, the multi-criteria information is fused to form a comprehensive criterion for small current grounding fault. Finally, the simulation model is constructed in DigSilent/PowerFactory, and the simulation waveforms under 1000 random fault scenarios are tested. The results show that the correct rate of the proposed method is 90.6 %, and it has a high correct rate in different fault scenarios, which is better than a single criterion, which verifies the effectiveness and superiority of the proposed method.

Jinchuan (China) (CN), China Agricultural University (CN)
Climate action
Openalex Percentile: Top 61%
Advanced Decision-Making Techniques
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