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Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching

Author

Listed:
  • Mingyue Tan
  • Jiming Li
  • Xiangqian Chen
  • Xuezhen Cheng

Abstract

To improve the reliability of power grid fault diagnosis by enhancing the processing ability of uncertain information and adequately utilizing the alarm information about power grids, a fault diagnosis method using intuitionistic fuzzy Petri Nets based on time series matching is proposed in this paper. First, the alarm hypothesis sequence and the real alarm sequence are constructed using the alarm information and the general grid protection configuration model, and the similarity of the two sequences is used to calculate the timing confidence. Then, an intuitionistic fuzzy Petri Nets fault diagnosis model, with an excellent ability to process uncertain information from intuitionistic fuzzy sets, is constructed, and the initial place value of the model is corrected by the timing confidence. Finally, an application of the fault diagnosis model for the actual grid is established to analyze and verify the diagnostic results of the new method. The results for some test cases show that the new method can improve the accuracy and fault tolerance of fault diagnosis, and, furthermore, the abnormal state of the component can be inferred.

Suggested Citation

  • Mingyue Tan & Jiming Li & Xiangqian Chen & Xuezhen Cheng, 2019. "Power Grid Fault Diagnosis Method Using Intuitionistic Fuzzy Petri Nets Based on Time Series Matching," Complexity, Hindawi, vol. 2019, pages 1-14, July.
    • Handle: RePEc:hin:complx:7890652
    DOI: 10.1155/2019/7890652
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    References listed on IDEAS

    as
    1. Jiming Li & Xiaolin Zhu & Xuezhen Cheng, 2018. "Sensor Fault Diagnosis Based on Fuzzy Neural Petri Net," Complexity, Hindawi, vol. 2018, pages 1-11, October.
    2. Rong Jia & Fuqi Ma & Jian Dang & Guangyi Liu & Huizhi Zhang, 2018. "Research on Multidomain Fault Diagnosis of Large Wind Turbines under Complex Environment," Complexity, Hindawi, vol. 2018, pages 1-13, July.
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    Cited by:

    1. Jianhua Zhang & Quanmin Zhu & Yang Li, 2019. "Convergence Time Calculation for Supertwisting Algorithm and Application for Nonaffine Nonlinear Systems," Complexity, Hindawi, vol. 2019, pages 1-15, October.

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