TUNING OF UNIFIED POWER FLOW CONTROLLER (UPFC) USING PSO AND NSGA-II INVESTIGATIONS

Abstract

This paper describes, tuning of Unified Power Flow Controller (UPFC) using evolutionary algorithm to reduce the electro-mechanical oscillations in power systems. This UPFC tuning is formulated as single and multi-objective optimization problem, to minimize the objective function considered by modulating the control parameters. The objective function considered for this work is Integral Squared Error (ISE) of change in speed deviation and Integral Squared Error (ISE) of control signal (u) under different operating conditions. Time domain simulation and Eigen value analysis are carried out to show the effectiveness of the proposed method. The optimal parameters and objective function values obtained with single and multi-objective algorithms (PSO and NSGA-II) are evaluated and the benefits of multi-objective optimization in FACTS controller tuning is explained. Simulation result reveals that the Non-dominated Sorting Genetic Algorithm-II based damping controller damp out oscillations quickly with minimum control input as compared with Particle Swarm Optimization based controller without compromising the stability of system.