Implementing Fuzzy Reasoning Petri-Nets for Fault Section Estimation

Fuzzy reasoning Petri-nets (PNs) is a promising technique to tackle the complexities of power system fault section estimation. This paper addresses several key issues in implementing fuzzy reasoning PNs for fault section estimation, which include optimal design of structure of diagnosis models to avoid large matrix size, utilization of fuzzy logic parameters to effectively handle uncertainties, realization of matrix execution algorithm to achieve parallel reasoning and adaptability, and integration of more reliable input data to enhance estimation accuracy. Case studies are presented to demonstrate the estimation capability under complex scenarios. An implementation solution residing in a control center is proposed.