Probabilistic approach for fault-section estimation in power systems based on a refined genetic algorithm

A systematic and mathematically sound model and a refined genetic algorithm (RGA) based method for fault-section estimation in power systems is proposed. First, the probabilistic causality relationship among section fault, protective relay action and circuit breaker trip is formulated as a probabilistic causality matrix. Secondly, the well-developed parsimonious set covering theory is applied to the fault-section estimation problem, and a 0–1 integer programming model is then obtained. Thirdly, a RGA-based method for fault-section estimation is developed by using information on operations of protective relays and circuit breakers. The proposed method is versatile and can deal with uncertainties in fault-section estimation, such as protective relay failures and/or malfunction and circuit breaker failures and/or malfunction. Test results for a sample power system have shown that the probabilistic approach developed for fault-section estimation is feasible and efficient.