A multi-criteria optimization technique for SSSC based power oscillation damping controller design

Abstract

In this paper, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) technique is applied to obtain Pareto optimal set of solutions pertaining to the tuning of lead-lag structured SSSC-based stabilizer. The design objective is to get maximum damping (performance) with minimum control effort (cost). Further a fuzzy based membership function value assignment method is employed to choose the best compromise solution. Simulation results are presented under various loading conditions and disturbances for various control signals to show the effectiveness and robustness of the proposed approach. The effectiveness and superiority of the proposed design approach are illustrated for both single machine infinite bus and multi-machine power systems by comparing the proposed approach with some recently published single objective and evolutionary multi-objective approaches such as Differential Evolution (DE), Particle Swarm Optimization (PSO) and Multi-objective Genetic Algorithm. It is observed that the proposed approach yields superior damping performance compared to some recently published approaches.

Keywords

• Power system stability
• Multi-criteria optimization
• Pareto optimal set
• Static synchronous series compensator
• Non-dominated sorting genetic algorithm-II