Optimal location and size determination of FACTS devices by using multiobjective optimal power flow

This paper proposes an algorithm based on nondominated sorting genetic algorithm (NSGA-II) with the feature of adaptive crowding distance for solving multiobjective optimal power flow (MOOPF) problem to find the optimal location and capacity of FACTS devices in power system. The problem is formulated as mixed integer one with both continuous and discrete control variables. Two types of FACTS devices (TCSC and SVC) are modeled and analyzed to improve the steady state performance of power system. The performance of the proposed algorithm has been tested on IEEE-30 bus systems. The results demonstrate that the proposed approach is quite efficient in finding optimal solutions.