Contingency Constrained Optimal Power Flow by Hybrid Optimization Technique Using FACTS Device

Abstract

Optimization algorithms are very important for the Optimal Power Flow (OPF). They could be divided into two classes: traditional local search methods and heuristic global ones. Interior point (IP) algorithm has been known as one of the most prominent and fastest method, but its local exploitation characteristic leads to the fact that it could be easily trapped by local optimum. However, heuristic methods such as Adaptive Particle Swarm Optimization (APSO) possess better convergence quality although their convergence speed is not good enough. This paper presents an Interior point method (IPM) and Adaptive particle swarm optimization (APSO) based hybrid method to solve the contingency constrained optimal power flow (OPF) in power systems incorporated with Flexible Ac Transmission Systems (FACTS). A versatile FACTS device TCPS (Thyristor controlled phase shifter) is considered. In the solution process APSO coupled with IPM to keep the power flows within their security limits. This Hybrid OPF algorithm with TCPS effectively relieves line flow violations under different single line contingencies. Severity Index is used as an objective function to be minimized to improve the security of the power system. The efficiency of proposed algorithm is illustrated by carrying simulation studies on IEEE 30 bus system .This analysis reveals that the proposed algorithm is quite simple and efficient for solving OPF problem.