ALLEVIATION OF LINE OVERLOADS UNDER CONTINGENCY BY OPTMAL UTILISATION OF FACTS DEVICES USING EVOLUTIONARY COMPUTATION TECHNIQUES

This paper proposes the evolutionary computational techniques for determining the most suitable locations and settings for installing the Flexible AC Transmission (FACTS) devices, Thyristor Controlled Series Capacitors (TCSC) and Unified Power Flow Controllers (UPFC), to eliminate line overloads under single contingency in a power system. The mostly affected lines of the system during single line outage are ranked using an index called Contingency Severity Index. To find the best locations among the ranked lines to install the FACTS devices, and to determine the settings of those devices, an optimization problem is formulated and solved using two evolutionary computation techniques, real coded Genetic Algorithm (RGA) and Particle Swarm Optimization (PSO). The reactance model for TCSC and the decoupled model for UPFC are considered for this work. Simulated Binary Crossover (SBX) and Non-uniform polynomial mutation are employed to improve the performance of the Genetic Algorithm used. Simulations are performed on IEEE 6-bus, 30-bus and 118-bus test systems. The results are compared in terms of improved system security before and after placing the FACTS devices and the performance of both techniques are analyzed.