Open AccessMethod of power grid fault diagnosis using intuitionistic fuzzy Petri nets
Author(s) -
Zhang Xu,
Yue Shuai,
Zha Xiaobing
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0471
Subject(s) - petri net , computer science , fault (geology) , data mining , fuzzy logic , alarm , electric power system , reliability engineering , stochastic petri net , artificial intelligence , power (physics) , algorithm , engineering , physics , quantum mechanics , seismology , geology , aerospace engineering
The uncertainty of alarm information in power grids can lead to incorrect diagnosis of faults. The authors propose a method for diagnosing power grid faults that considers the uncertainty of alarm information using intuitionistic fuzzy logic. To consider the influence of the uncertainty of alarm information in fault diagnosis, an intuitionistic fuzzy set is used to represent the certainty and the uncertainty of alarm information. Using topological analysis and the logical relationships among electrical devices, protective actions, and circuit breaker trips, the authors establish a diagnostic model for power systems based on intuitionistic fuzzy Petri nets. The certainty and the uncertainty of electrical device fault events are calculated using the reasoning method for intuitionistic fuzzy Petri nets. The results for some test cases show that this method can effectively diagnose complex faults in power systems when multiple components operate incorrectly in the complicated data environment and the information is not trusted.