PSO-Based Optimal Design of Power System Stabilizers for Multi-Machine Power System

Low-frequency electromechanical oscillations constitute a major risk to power system stability, and if undamped, can cause wide-spread blackouts. The most common method of providing the necessary damping is through the use of power system stabilizers (PSS), which control the generator excitation system. Traditional fixed-parameter power system stabilizers (CPSS) employ linear models and are based on a single operation point. This makes them ineffective at different load situations as well as at handling severe disturbances. This paper presents a study on designing an optimal CPSS based on particle swarm optimization (PSO). The PSO algorithm will tune the CPSS parameters including the gain and the lead-lag time constants by placing the poles of the closed loop system at an optimal location inside a specified D-shaped region of the s-plane. The proposed approach will be demonstrated on the IEEE ۹-bus, ۳-machines power system model subjected to a three-phase short circuit fault under light, normal, and heavy load scenarios. Comparative analysis of the simulations will prove that the PSO tuned PSS, referred to as PSO-PSS, out-performs the traditional PSS as well as the Grey Wolf Optimizer PSS (GWO-PSS) in terms of overshoot, settling time, and zero steady state error. The quantitative performance measures IAE and ITAE will show that PSO-PSS provides better damping capacity compared to CPSS and GWO-PSS.

کلیدواژه ها:

Power system stability ، Low-frequency oscillations ، Power system stabilizer ، Multi-Machine Power System ، Load conditions variation ، Particle swarm optimizati