Fault Diagnosis of Power Systems Based on Temporal Constrained Fuzzy Petri Nets

• Main Authors: Biao Xu, Xin Yin, Xianggen Yin, Yikai Wang, Shuai Pang
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Power system; fault diagnosis; fuzzy reasoning; temporal constraint; TCFPNs
• Online Access: https://ieeexplore.ieee.org/document/8769967/

Modern power systems are equipped with comprehensive protective devices to remove the fault section, and the fault diagnosis problem is to interpret the alarms of the protective devices and estimate the fault section. To deal with the uncertainty and temporal constraint of the alarms, a novel fault diagnosis model based on the temporal constrained fuzzy Petri nets (TCFPNs) is proposed in this paper. The truth degree and the timing contribute of the alarms are introduced into the graphic model of the TCFPNs, and the matrix algorithm, considering both the fuzzy reasoning and temporal reasoning, is carried out to obtain the fault probability as well as the time point constraint of each candidate section. The developed approach is performed on different test systems for case studies, and the results demonstrate the feasibility, efficiency, and fault tolerance of the method.