A novel optimized dynamic fractional-order MPPT controller using hunter pray optimizer for alleviating the tracking oscillation with changing environmental conditions

Introducing new control strategies in the photovoltaic (PV) system to continuously harvest the maximum power with the changes in environmental conditions is a crucial issue. Therefore, this paper proposes an efficient maximum power point tracker (MPPT) using the perspective of fractional calculus to provide an accurate dynamic response to the rapid changes in environmental conditions. The proposed control scheme is an integration between the fractional proportional–integral (FPI) controller and dynamic variable fractional-order perturb and observe (P&O) MPPT. To optimally identify the proposed MPPT controller parameters, a novel hunter-pray optimizer (HPO) is implemented as it is featured by its efficient balance between exploration and exploitation capacity. The proposed MPPT controller is examined with a series of experiments under dynamically changed environmental conditions. Furthermore, a detailed comparison is conducted versus a set of state-of-the-art including; incremental conductance (INC), basic P&O, MPPT-based particle swarm optimizer(PSO), MPPT-based Grey Wolf Optimizer(GWO), and MPPT-based cuckoo search algorithm (CSA). The results prove that the proposed MPPT is capable to track the global maximum generated power with a notable steady-state response and is almost free of oscillations which ensures an optimal adaptive dynamic performance in response to the rapid variation in the environmental conditions. Moreover, the proposed approach affirms its superiority compared to the set of state-of-the-art techniques in providing the highest maximum power levels in the shortest conversion time. The outcomes provide proof of the remarkable impacts of integrating fractional calculus in enhancing the dynamic response of the proposed MPPT because of the extra degree of freedom that enhance the flexibility of the MPPT.