Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12–14, 2024, Ningbo, China

Research Article

Research on Abnormal Signal Identification Algorithm of Distribution Network Operation Based on Big Data Mining

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  • @INPROCEEDINGS{10.4108/eai.12-1-2024.2347156,
        author={Yang  Li and Sheng  Liu and Ziyi  Zhao and Lin  Yan and Zhaohua  Hu},
        title={Research on Abnormal Signal Identification Algorithm of Distribution Network Operation Based on Big Data Mining },
        proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12--14, 2024, Ningbo, China},
        publisher={EAI},
        proceedings_a={BDEDM},
        year={2024},
        month={6},
        keywords={big data mining; power distribution; power grid; operation; abnormal signal; identification; algorithm},
        doi={10.4108/eai.12-1-2024.2347156}
    }
    
  • Yang Li
    Sheng Liu
    Ziyi Zhao
    Lin Yan
    Zhaohua Hu
    Year: 2024
    Research on Abnormal Signal Identification Algorithm of Distribution Network Operation Based on Big Data Mining
    BDEDM
    EAI
    DOI: 10.4108/eai.12-1-2024.2347156
Yang Li1,*, Sheng Liu1, Ziyi Zhao1, Lin Yan1, Zhaohua Hu1
  • 1: Shenzhen Power Supply Co., Ltd
*Contact email: 1828937@qq.com

Abstract

Conventional algorithm for identifying abnormal signals of distribution network mainly uses ESD (extreme studied deviate test) to obtain signal time series, which is easily influenced by proximity clustering relationship, resulting in poor identification performance. Therefore, it is necessary to design a new algorithm for identifying abnormal signals of distribution network based on big data mining. That is, the abnormal signal of distribution network operation is collected, and the characteristics of abnormal signal of distribution network operation are extracted by big data mining, and the optimization algorithm of abnormal signal identification of distribution network operation is generated, thus realizing the identification of abnormal signal of distribution network operation. The experimental results show that the designed algorithm for identifying abnormal signals of distribution network operation has good recognition performance, high accuracy, recall and F1 score, and it is reliable and has certain application value, which has made certain contributions to reducing the operation risk of distribution network.