Knowledge representation and general Petri net models for power grid fault diagnosis

Abstract

This study deals with the idea that comprehensive knowledge representation should be established for fault diagnosis. Sufficient grid fault information including the network topology and protection knowledge are used with a diagnostic algorithm. In this way, the fault diagnosis programme not only facilitates accurate judgment of fault sections for which many kinds of information are available but also optimises knowledge to simplify the fault diagnosis method. Petri nets are used for logical reasoning on the basis of knowledge representation, which can be used to judge fault elements accurately even when the protective relays and circuit breakers malfunction. It was proved through experimentation here that this method meets the requirements of real-world diagnosis. The programme can be used as an interface to the self-healing mechanism of a smart grid. This study also posits that the smart grids should be constructed on the basis of knowledge representation for every subsystem.