Dynamic Load Frequency Regulation in Two Area Power Systems via Pelican-Optimized PID Control

Abstract

This article presents Pelican Optimization Algorithm (POA) for Load Frequency Control (LFC) in two area interconnected power systems. Extensive simulations in MATLAB indicate that the POA surpasses numerous established metaheuristic optimization algorithms, involving the Grey Wolf Optimizer (GWO), Hippopotamus Optimization Algorithm (HOA), Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Teaching-Learning Optimization Algorithm (TLOA) and Whale Optimization Algorithm (WOA) regarding the mitigation of frequency deviations and improvement of dynamic response. The robustness of the POA based LFC is validated under scenarios of random load disturbances, varying system parameters, typical power system nonlinearities like generation rate constraints (GRC) and governor deadband (GDB), and with renewable energy sources. The studies highlighted in the article demonstrate superior adaptability and effectiveness of POA to optimally tune the gains of PID controller. The statistical analysis demonstrate that the proposed POA achieves convergence to the global optimum with reduced execution time (~12% less than the second best HOA) and exhibits lower mean (~15.2% less than the second best SSA) and standard deviation (~3.09% less than the second best HOA) over multiple independent runs. Stability analysis using Bode plots confirms that the proposed control strategy maintains adequate stability margins.