Particle Swarm Intelligence Based Optimization Controller Applied to Two Area Interconnected Power Systems

Abstract

AbstractThis paper presents the optimal performance of Load Frequency control (LFC) in interconnected two-area power systems. Proportional–Integral (PI) controllers are commonly used for LFC systems in power industry. But the dynamic behaviors in the presence of variations in load changes with different operating conditions are needed to be improved. This paper proposes Particle Swarm Optimization (PSO) based Load Frequency Control for improving the dynamic performance of the system. A two area interconnected power system, having different generating units is considered to be equipped with Proportional Integral and Derivative (PID) controller. PSO algorithm is implemented to search the optimal controller parameters by minimizing the time domain objective function. The performance of the proposed PID controller has been evaluated by the performance of the conventional controller and the controller tuned by Genetic algorithm (GA) in order to demonstrate the superior efficiency of the proposed PSO algorithm. Simulation results proved that the proposed algorithm is moderately fast algorithm and yields true optimal gains with minimum overshoot, minimum undershoot, minimum rise time and minimum settling time for any power system. Furthermore, the dynamic behavior of the proposed controller under variations of system parameters and load changes are better than that of conventional and GA controllers.KeywordsLoad frequency controlGenetic algorithmOptimization techniquePower systemParticle swarm optimization