A novel heuristic technique implemented with FOPI controller for dynamic power management in hybrid energy storage systems

Abstract This paper introduces a power management strategy (PMS) for photovoltaic (PV) and hybrid electrical energy storage (HEES) systems, combining batteries and supercapacitors (SCs). The proposed strategy employs a fractional-order proportional-integral (FOPI) controller, optimised using a novel African Vultures Optimization Algorithm (AVOA), Hybrid Particle Swarm Optimization-Grey Wolf Optimizer (HPSO-GWO), and Grey Wolf Optimizer (GWO). The controller optimised with the new AVOA and HPSO-GWO features shows more effective and improved robustness than conventional algorithms. These findings demonstrate the performance of the PMS and the advantages of AVOA and HPSO-GWO-based tuning strategies for HEES system control. The system’s robustness and efficiency were validated through simulations under various solar irradiance, resistive load conditions, fixed temperature, and pulsed loads in real-time, demonstrating improved transient response and extended battery life. The optimised PMS effectively balances energy distribution, reduces battery stress, and enhances system stability, proving superior to traditional methods in dynamic and complex environments. Furthermore, the effectiveness of the suggested strategy is demonstrated by the decrease in settling time, even with fluctuations in resistive load, fixed temperature, pulsed load, and irradiation.