Voltage Contingency Ranking of a Practical Power Network Using Hybrid Neuro-Fuzzy System

Maintaining power system security is a challenging task for power system engineers. The idea is to shortlist critical contingencies from a large list of contingencies and to rank the contingencies expected to drive the system towards instability. Corrective measures can then be planned to save the system from collapse and blackout. This paper presents a simple multi-output fuzzy-neural network for contingency ranking in a power system. A fuzzy overall performance index (FOPI), formulated by combining i) voltage violations and ii) voltage stability margin is being employed in this paper for composite ranking of contingencies. The proposed approach is very effective in handling contingencies lying on the boundary between two severity classes. Feature selection using fuzzy curves has been employed to reduce the dimension of the network. The performance of the proposed method has been tested on a 69-bus practical Indian power system.