Fuzzy logic approach in power system fault section identification

Great emphasis has been put on applying expert systems for transmission system fault diagnosis. However, very few papers deal with the unavoidable uncertainties that occur during operation involving the fault location and other available information. The paper proposes a method using fuzzy sets to cope with such uncertainties. A fuzzy expert system is developed, which requires much less memory to store an active database than that used by conventional rule-based expert systems. The fuzzy expert system identifies two basic network section sets, S_healthy for the healthy subnetwork and S_island for the fault islands, using the postfault status of circuit breakers and relays. It then conducts inference to determine the most likely fault sections and the associated fault sequences. Two case studies are provided to demonstrate salient features of the proposed approach, and to compare results both with a conventional rule-based expert system and a refined genetic algorithm. The proposed fuzzy expert system can be operated either in a stand-alone manner, or as part of the overall architecture of a diagnosis system for parallel decision making