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Research on power grid fault diagnosis method based on multi-source heterogeneous data

Published: 31 July 2024 Publication History

Abstract

Traditional fault diagnosis methods can easily lead to problems such as "diagnosis blocking" and "curse of dimensionality". In order to improve the accuracy and reliability of traditional power grid fault diagnosis methods, an intelligent power grid fault diagnosis method based on multi-source data fusion of electrical quantities and switching quantities is proposed. This method first performs wavelet transformation on the fault current recording data to obtain the characteristic quantity of the electrical quantity of current; then normalizes the diagnosis results of the switching quantity to obtain the relative fault degree evidence corresponding to the switching quantity; and finally adopts an improved the D-S evidence theory fuses multi-source data of electrical and switching quantities and obtains the final diagnosis result. Actual power grid results show that the proposed fault diagnosis method can effectively improve the accuracy of fault diagnosis.

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 July 2024

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