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To realize an operation supporting expert system for large-scale power networks, two items are considered to be especially important. The first is inference speed and the other is an interface between an expert system and a conventional energy management system (EMS) or a SCADA system. To improve inference speed a dedicated artificial intelligence processor and a specific domain shell for real-time expert systems are adopted, and also reduction of rule-search space size is devised considering features of power networks. Tightly coupled interface and distributed database between a logic-program-based system and a procedural-program-beased system are desirable. An operation supporting system for a large-scale power network has been developed and installed in Fukuoka Integrated Control Center, Kyushu Electric Power Company. The system is configured of triple super-minicomputers with back-ended artificial intelligence processors, and also of dual micro-processor-based front-end-processors (FEPs). Knowledge-based functions, such as fault determination, restoration procedure generation, security monitoring and operation planning are installed in addition to conventional functions of an EMS and a SCADA system. The inference results and their inference speed are satisfactory.
Arita et al. (Mon,) studied this question.