Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets

Abstract

Abstract: Due to the advantages of Fuzzy reasoning Petri-nets(FPN)on uncertain and incomplete information processing. It is a promising technique to solve the complex power system fault-section estimation problem. Therefore, we propose a novel estimation method based on Adaptive Fuzzy Petri Nets (AFPN), in this algorithm, the AFPN is used to build a dynamic fault diagnosis fuzzy reasoning model, where the weights in fuzzy reasoning are decided by the incomplete and uncertain alarm information of protective relays and circuit breakers. The validity and feasibility of this method is illustrated by simulation examples. Results show that the fault section can be diagnosed correctly through fuzzy reasoning models for ten cases, and the AFPN not only takes the descriptive advantages of fuzzy Petri net, but also has learning ability as neural network.