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  • 标题:Study on Application of Fisher Information for Power System Fault Detection
  • 本地全文:下载
  • 作者:Shuping Cai ; Guohai Liu
  • 期刊名称:Bulletin of the Institute of Heat Engineering
  • 印刷版ISSN:2083-4187
  • 出版年度:2016
  • 卷号:98
  • 期号:3
  • 页码:274-280
  • 语种:English
  • 出版社:Warsaw University of Technology
  • 摘要:The ability to accurately detect power system faults is of vital importance for the purpose of isolating malfunctioning equipment and resuming normal operation as soon as possible after a fault occurs. People have used a variety of electric parameters as metrics to identify faults for a long time. The method proposed by this paper departs from the traditional approach by introducing Fisher information (FI) as a measure of the stability of electric signals and as a criterion for making fault decisions. In this way, a non-dimensional positive parameter is used as a single criterion to deliver fault detection for power distribution networks. Firstly, we simplified the formula of FI and then adopted a practical method for calculating values of FI. We demonstrated the application of FI to measure the stability of electric signals. Finally, we combined FI with wavelet analysis to propose a novel technique for phase selection of a power distribution network with a grounding short-circuit fault, namely the wavelet-based Fisher information (WFI). Simulation studies were then carried out to show the feasibility of the proposed method.
  • 其他摘要:The ability to accurately detect power system faults is of vital importance for the purpose of isolating malfunctioning equipment and resuming normal operation as soon as possible after a fault occurs. People have used a variety of electric parameters as metrics to identify faults for a long time. The method proposed by this paper departs from the traditional approach by introducing Fisher information (FI) as a measure of the stability of electric signals and as a criterion for making fault decisions. In this way, a non-dimensional positive parameter is used as a single criterion to deliver fault detection for power distribution networks. Firstly, we simplified the formula of FI and then adopted a practical method for calculating values of FI. We demonstrated the application of FI to measure the stability of electric signals. Finally, we combined FI with wavelet analysis to propose a novel technique for phase selection of a power distribution network with a grounding short-circuit fault, namely the wavelet-based Fisher information (WFI). Simulation studies were then carried out to show the feasibility of the proposed method.
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