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

Abstract

Stressed power systems, either due to increased loading or due to contingencies, often lead to situations where the systems are no longer remaining in security operating regions. Under such situations, the primary objective of the operator is to apply control actions to bring the systems back into the security operating regions. In the cases when systems are subjected to any kind of time delay or unavailability of control, systems may become unstable which is very dangerous situation for power systems. Flexible AC transmission systems (FACTS) devices can play very important role in power system security enhancement. 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. Due to the high capital investment of FACTS devices and to achieve a better utilization (satisfactory performance) of theses devices, it is necessary to locate these devices optimally in the power system. This paper mainly concerned with the enhancement of the system security against single contingencies via the optimal placement of TCSC. The paper deals with the application of two evolutionary optimization techniques namely, genetic algorithm (GA) and particle swarm optimization (PSO) for the optimal location and the optimal parameter setting of TCSC under single line contingency ( N − 1 Contingency). Contingency analysis is performed to detect and rank the severest line faulted contingencies in the power system. To validate the proposed techniques, simulations are performed on an IEEE 6-bus power system and an IEEE 14-bus power system. Encouraging results are obtained, which show that TCSC is one of the most effective series compensation devices that can significantly eliminate or minimize line overloads under 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.