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On Combined PSO-SVM Models in Fault Prediction of Relay Protection Equipment

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Abstract

Since there are no monitoring devices in relay protection equipment of substations, it takes up a lot of manpower and material resources in operation and maintenance (O&M), and the efficiency is very low. In this paper, we solve the giving fault prediction model by applying particle swarm optimization algorithm and support vector machine algorithm for relay protection equipment. The combined model was found to be able to establish the correlation between the variables more accurately and improve the prediction accuracy of the model by comparison. The simulation result shows that the prediction accuracy of the model is at least 91% for three different devices. The combined prediction model can not only provide strong technical support for the maintenance strategy of relay protection equipment but also improve the maintenance efficiency and reduce the failure rate of protection equipment.

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Data Availability

All data included in this study are available upon request by contact with the corresponding author.

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Acknowledgements

The authors are very grateful to Prof. Binwu Zhang from the Institute of Intelligent Optimization and Control of Hohai University for their enthusiastic guidance and constructive suggestions.

Funding

This paper is supported by the Science and Technology Project of State Grid Corporation Limited (SGJSCZ00KJJS2100747), in part by the National Nature Science Foundation of China (NSFC) under grant No.52077058.

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Authors and Affiliations

  1. Changzhou Power Supply Branch, State Grid Jiangsu Electric Power Co., Ltd, Changzhou, 213003, Jiangsu, China

    Huang Yuming, Luo Jiaohong, Ma Zhenguo, Tang Bing & Zhang Keqi

  2. College of Science, Hohai University, Changzhou, 213022, Jiangsu, China

    Zhang Jianyong

Authors
  1. Huang Yuming
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  2. Luo Jiaohong
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  3. Ma Zhenguo
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  4. Tang Bing
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Contributions

Y. Huang contributed to conceptualization and investigation; J. Luo contributed to methodology and data curation; B. Tang contributed to validation and project administration; Z. Ma contributed to formal analysis and writing—review and editing; K. Zhang contributed to resources and writing—original draft preparation; and J. Zhang contributed to visualization and funding acquisition and supervised the study. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Zhang Jianyong.

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Yuming, H., Jiaohong, L., Zhenguo, M. et al. On Combined PSO-SVM Models in Fault Prediction of Relay Protection Equipment. Circuits Syst Signal Process 42, 875–891 (2023). https://doi.org/10.1007/s00034-022-02056-w

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