FACTS allocation based on expected security cost by means of hybrid PSO

This paper proposes an approach to optimally allocate FACTS devices based on Expected Security Cost Optimal Power Flow (ESCOPF) under deregulated power system. The aims of the approach are both to minimize device investment cost and to maximize benefit defined as difference between Expected Security Cost (ESC) with and without FACTS installation. The expected cost includes operating cost not only under normal condition but also under contingencies along with their associated probabilities to occur. Furthermore, this cost considers compensation for generation power deviation and load interruption. FACTS devices re-setting is the first attempt to be executed in order to minimize the operating cost. Then, generations re-dispatch and load shedding are the second and the third priority actions to minimize ESC. Interaction among multiple FACTS devices in achieving minimum expected cost under both normal condition and contingencies is also considered in this paper. The overall problem is solved using both Particle Swarm optimization (PSO) for attaining optimal FACTS allocation as main problem and Sequential Quadratic Programming (SQP) for solving optimal power flow as sub optimization problem.