Allocation of multi-type FACTS devices using multi-objective genetic algorithm approach for power system reinforcement

Abstract

This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission systems (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensator (TCSC) and static var compensator (SVC) are the utilized FACTS devices. Our objectives are: active power loss reduction, new introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, are considered in the optimum allocation. A multi-objective genetic algorithm (MOGA) is used to approach the Pareto-optimal front (non-dominated) solutions. In addition, the estimated annual load profile has been utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. IEEE 14-bus Network is selected to validate the performance and effectiveness of the proposed method.