Sustainable Energy Management of PV–Battery–Supercapacitor Systems via Metaheuristic-Optimized Coordinated Dual-Loop Control

In photovoltaic-based hybrid energy storage systems (PV–HESS), rapid power transients accelerate battery degradation, directly reducing the operating lifetime and sustainability of renewable power resources. To address this issue, the current study proposes an optimal coordinated framework for the simultaneous and coordinated tuning of battery and supercapacitor current-loop proportional–integral (PI) controllers. The proposed framework treats the four PI gains of the battery and supercapacitor controllers as a unified optimization problem, applying five metaheuristic algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gazelle Optimization Algorithm (GOA), Artificial Protozoa Optimizer (APO), and White Shark Optimization (WSO). The optimization problem is directly coupled with a full nonlinear MATLAB 2022b/Simulink PV–HESS model, capturing the dynamic interactions among the PV array, bidirectional converters, DC-link capacitor, storage units, and load. A combined Integral of Time-weighted Absolute Error (ITAE) objective function is used to minimize current tracking errors, ensuring the supercapacitor absorbs fast power fluctuations while shielding the battery from high-frequency thermal and electrical stress. The controllers are evaluated across four operating scenarios involving steady irradiance shifts, rapid irradiance fluctuations, load disturbances, and a simultaneous irradiance drop from 1000 W/m2 to 400 W/m2 with a 33% load increase. The results confirm stable DC-link regulation and effective power sharing. Specifically, APO delivers superior performance in the high-stress scenario, GOA minimizes transient-error indices, and GA achieves the lowest DC-link voltage RMSE. These findings demonstrate that coordinated tuning effectively balances high-frequency dynamics, extending battery service life and enhancing the long-term operational sustainability of solar microgrid storage.