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Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21–22, 2019, Proceedings, Part I

Research Article

Fault Feature Analysis of Power Network Based on Big Data

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  • @INPROCEEDINGS{10.1007/978-3-030-36402-1_15,
        author={Cai-yun Di},
        title={Fault Feature Analysis of Power Network Based on Big Data},
        proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2019},
        month={11},
        keywords={Big data environment Power network Fault characteristics Analytical method},
        doi={10.1007/978-3-030-36402-1_15}
    }
    
  • Cai-yun Di
    Year: 2019
    Fault Feature Analysis of Power Network Based on Big Data
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-36402-1_15
Cai-yun Di1,*
  • 1: State Grid Jibei Electric Power Company Limited Skills Training Center
*Contact email: cjj998799@163.com

Abstract

During the operation of the power network, there was a sharp change in current and voltage at the time of failure, which made it difficult for the grid operators to quickly and accurately determine the fault. This paper proposed a big data-based power network fault feature analysis method design. Taking the symmetrical fault component method as the main analysis method, a two-phase short-circuit equivalent model was constructed by accurately analyzing the fault characteristics of the power network, and the fault features were detected and located by the big data network preprocessor. The experimental results shown that the big data power network fault feature analysis method could effectively feedback and locate the fault location and complete the maintenance of the power network in time.

Keywords
Big data environment Power network Fault characteristics Analytical method
Published
2019-11-29
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-36402-1_15
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