An object-oriented expert system for power system alarm processing and fault identification

Alarm processing is a traditional feature of energy management systems (EMS) and has not changed significantly over several generations of SCADA design. However recent applications of artificial intelligence have dramatically altered the methods of handling this information. This paper describes two parts of a project carried out at the University of Dundee for Scottish Hydro-Electric plc (HE) on the use of an artificial intelligence system for alarm processing and fault diagnosis. The first part of the project was an overview and comparison study of three real-time object-oriented toolkits: Muse, Kappa and Nexpert Object. The study is based on the capabilities of such toolkits to handle the power system alarm processing integration with external programs and real-time databases, portability, price and execution speed. Some advantages and drawbacks of each toolkit are also pointed out. The second part of the project was the implementation of an object-oriented expert system using the KappaPC toolkit operating on a 486 IBM compatible PC under Microsoft Windows 3.1. The structure of the object-oriented expert system captures the heuristic knowledge used for power system operation. The knowledge-base is automatically updated by the existing SCADA system as the power system status changes. The paper also describes the features of the real-time object-oriented expert system which includes the need for fast deep-level reasoning, easy maintainability of the object-oriented programming and the end user´s interface