Optimal allocation of SVC to enhance Total Transfer Capability using Hybrid Genetics Algorithm and Sequential Quadratic Programming

This paper concentrates on studying the effects of SVC controller on Total Transfer Capability (TTC) of power transactions between source and sink areas using Hybrid Genetic Algorithm-Sequential Quadratic Programming (GA SQP). GA-SQP is a novel algorithm in power systems. The proposed algorithm is used to determine optimal placement of SVC controller and solving optimal power flow (OPF) to enhance TTC simultaneously. The proposed OPF is used to evaluate feasible TTC value within real and reactive power generation limits, line thermal limits, voltage limits and SVC operation limits. A 5 bus test system is used to demonstrate the effectiveness of the GA-SQP algorithm to enhance the TTC of the system. The results clearly indicate that introduction of SVC with proper parameters and location could enhance TTC.

I. Introduction

In recent years deregulation and reconstruction of power systems introduce new challenges for electricity providers and consumers, challenges which didn't receive any attention before. Now all transmission providers agree to use transmission lines near their limit conditions, but there are many limitations to do that; the most important is stability and voltage lower and upper limitations, thermal limitation is considerable. Due to physical constraints on circuit impedance and phase angle of nodal voltage, most high voltage transmission lines are operating below their thermal ratings [1]. For the first time in 1991, FACTS devices were used in transmission lines. They had great effects on operation of transmission systems, deserving voltage constraints, thermal constraints and stability [2].