Frequency Control of Renewable‐Based Microgrids With Storage Subsystems Using an Improved Exponential Distribution Optimizer

This article introduces an advanced optimization‐based control framework for a hybrid microgrid (MG) system that includes renewable energy sources and energy storage components. An optimal controller is designed by tuning its parameters through an improved exponential distribution optimizer (IEDO), aimed at addressing the load frequency control (LFC) problem, essential for maintaining system stability amidst intermittent generation and stochastic disturbances. The MG comprises photovoltaic (PV) generation, wind turbines, battery storage systems (BSSs), and flywheel storage systems (FSSs), operating reliably despite variable loads and renewable uncertainties. The proposed IEDO enhances conventional exponential distribution optimizer (EDO) through three modifications: it integrates a differential evolution (DE)/rand/1‐inspired global search equation to boost exploration and prevent premature convergence; introduces a dimensional perturbation module (DPM) for selective decision variable updates, improving convergence accuracy; and employs a Bounce Out Operation (BOO) to reinitialize some solutions, maintaining diversity and allowing escape from local optima. The effectiveness of the proposed IEDO‐based control strategy is validated through extensive simulations under various operating scenarios, including load variations and renewable intermittency. Comparative results demonstrate that the proposed method achieves superior frequency regulation, reduced steady‐state error, faster dynamic response, and improved robustness compared to existing optimization techniques.