Method for Identifying Abnormal Data in Distribution Network Operation

doi:10.11930/j.issn.1004-9649.202302051

Abstract

Abstract: In order to improve the recognition accuracy of abnormal data of distribution network operation, a novel method for identifying abnormal data of distribution network operation is proposed based on k-means improved firefly algorithm. Firstly, the distribution network operation data is collected in the distribution network information system, and such treatments as data cleansing, consolidation and characterization are performed. Then, the optimal clustering of the improved firefly algorithm based on k-means is used to obtain the sample characteristic curves and sample classification, and the band-pass matrix is obtained to determine the abnormal data points, so the identification of abnormal data of distribution network operation is completed. The results show that the proposed method has a higher accuracy in identifying abnormal operating data for different combinations of electrical equipment states.

Key words: abnormal data of distribution network operation, abnormal recognition, firefly algorithm, optimize clustering

LIN Yuhuan, HAO Fangzhou, LI Baixin, HUANG Bo. Method for Identifying Abnormal Data in Distribution Network Operation[J]. Electric Power, 2023, 56(9): 134-139.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202302051

https://www.electricpower.com.cn/EN/Y2023/V56/I9/134

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