Evolutionary optimization techniques for optimal location and parameter settings of TCSC under single line contingency

Flexible AC transmission systems (FACTS) devices are optimally placed in the power system in order to maximize the system security. One of the most effective FACTS devices is the thyristor controlled series capacitor (TCSC) which can smoothly and rapidly change its apparent reactance according to the system requirements. This paper deals with the application of two evolutionary optimization techniques namely, genetic algorithm (GA) and particle swarm optimization (PSO) for finding the optimal location and the optimal parameter settings of TCSC under single line contingency (N-1 contingency). Contingency analysis is performed to detect and rank the severest line faulted contingencies in a power system. To validate the proposed techniques, simulations are performed on an IEEE 6-bus power system and an IEEE 14-bus power system. The obtained results are encouraging, and show that TCSC is one of the most effective series compensation devices that can significantly eliminate or minimize line overloads against single contingencies. Also the results indicate that both GA and PSO techniques can easily and successfully find out the optimal location and the optimal parameter settings of TCSC.

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