Optimal SVC Placement in Electric Power System Using NSGA-II

Abstract

This paper proposes non dominated sorting genetic algorithm (NSGA-II) with a feature of adaptive crowding distance for obtaining optimal location and sizing of Static Var Compensators (SVC) to minimize real power losses (RPL) and load bus voltage deviation (VD) considering critical contingencies. The voltage security of the power system is also analyzed for all placements of SVCs at respective location computed. Finally, after compression of optimal power loss, load bus voltage deviation along with voltage security following by simulation of critical contingency the most appropriate location and sizing of SVC is determined. While obtaining the optimal location and sizing of SVC, single line outages are considered as contingencies and voltage limits for the load buses are considered as security constraints. The effectiveness of proposed approach has been demonstrated on IEEE 30-bus test system. The results obtained for proposed algorithm are optimistic and reveal the capability of the NSGA-II to generate well-distributed non-dominated Pareto front.