An abductive fuzzy knowledge based system for fault diagnosis in a power system

Abstract

This paper presents the design and evaluation of a novel, Al (artificial intelligence) based alarm processing and fault diagnosis system, for a 132 kV/12 bus-16 line sample power system. The work has been conducted in conjunction with Scottish Hydro Electric PLC. The fault diagnosis system is based on a hybrid object-oriented AI technique. The method developed utilises abductive inference. This technique is demonstrated to realise some improvements when compared with fuzzy logic and takes into account the current practical limitations in the design. The method is based on processing SCADA (supervisory control and data acquisition) messages, extending the arrangement of the knowledge acquisition process and applicability of circuit breakers and relays. The potential benefits and implications of adopting such an abductive fuzzy knowledge based system are demonstrated in this research, and include a user friendly inference engine, adaptability, and KBS update.