A COMPUTER-ASSISTED INTELLIGENT STORM OUTAGE EVALUATOR FOR POWER DISTRIBUTION-SYSTEMS

The lower voltage part of the power distribution system (primary and secondary sub-systems) does not have the provision for real-time status feedback, and as a result evaluation of outages is an extremely difficult task, especially during system emergencies caused by tornadoes. and ice-storms. In this paper, a knowledge based approach is proposed for evaluation of storm related outages in the distribution systems. 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 to generate 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. KEY WORDS Storm damage evaluation, fault detection, distribution automation, distribution systems, knowledge based systems, expert systems. © 1990 IEEE