Genetic Algorithm Technique for Social Welfare Improvement Using FACTS & Generation Rescheduling

Abstract: This paper presents a framework to carry out an novel method based Optimal Power Flow (OPF) for transmission congestion management in deregulated power system using Thyristor Controlled Series Capacitor (TCSC) and Generation Rescheduling. In the deregulated environment, some generators may not be willing to participate in the congestion management process for their own economic interest or some other operational constraints. By using Generator Sensitivity (GS), we select generators actually participating in congestion alleviation. The research presented in this paper aims to maximize total system social welfare and alleviate congestion by best placement and sizing of TCSC device. The proposed approach makes use of the Genetic Algorithm (GA) to optimise the schedule of Generating Companies (GenCos), Distributing Companies (DisCos) and TCSC location and size based on severity power index, while the Newton–Raphson algorithm minimizes the mismatch of the power flow equations. Simulation results on the modified IEEE 30-bus test systems (with line flow constraints, before and after the compensation) are used to examine the impact of TCSC on the total system social welfare improvement. The results show clearly the effectiveness of suggested method.

Keywords: Congestion management, Generator Sensitivity, Severity power index, FACTS, TCSC, Genetic Algorithm.