A computer assisted intelligent storm outage evaluator for power distribution systems

A knowledge-based approach for evaluating storm-related outages in distribution systems is proposed. At the outset, binary voltage sensors capable of transmitting the real-time voltage on/off symptoms are recommended to be installed at strategic locations in the distribution system. A semantic network model has been developed to represent the knowledge of the distribution system faults and their associated symptoms. The real-time voltage symptoms, transmitted by the sensors, serve as the basic input to the semantic network model in generating fault hypotheses. A rule base, incorporating temporal and topological knowledge of symptoms and system operators' heuristics, is used by the inference mechanism to determine the actual faults from the hypotheses set. The results suggest that the fault types and their exact sections can be diagnosed accurately.<
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