Use of intelligent search methods in performing sensitivity analysis of power system reliability indices

This work introduces a technique to reduce the search space in evaluating the sensitivity of the well known reliability indices of power systems with respect to component parameters and system operating limits. In performing the sensitivity analysis, the computation time burden is of concern. A heuristic technique based on maximum capacity flow of the transmission lines was used in truncating the state space by identifying the definite failure subspace. Minimum generation vector technique was utilized to prune the definite success subspace. The failure states in the unclassified subspace were discovered using binary Particle Swarm Optimization, PSO, technique. From the definite failure subspace and the failure states that are discovered by the binary PSO, the sensitivity of the reliability indices were calculated. This method was applied on the IEEE RTS and it gave promising results.