A knowledge based approach to evaluate storm related outages in power distribution systems

A computer-assisted intelligent storm outage evaluator (CAISOE) featuring real-time status information and system operators´ heuristics is proposed. The CAISOE system can detect single and multiple faults of any type on any section of the distribution system, and can serve as an offline consultation system to the distribution system operators. At the outset, binary voltage sensors capable of transmitting the real-time voltage ON/OFF symptoms are installed at strategic locations of the distribution system. A semantic network model represents 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 generation of possible 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