Abstract
Lately, the world is looking forward to replacing fossil fuels with renewable energy resources. Photovoltaic (PV) is benefited among renewable energies by its simple design, easy fitting, and fast expansion. For proper selection of controller gains for the PV system's control unit, this paper introduces a new hybrid optimization algorithm. The proposed optimization technique is applied to a PV system to enhance its performance under dynamic irradiance. The introduced hybrid optimization approach includes two optimization algorithms which are Teaching Learning Based Optimization (TLBO) and Equilibrium Optimizer (EO). Moreover, this paper presents a comparison with different optimization algorithms (Harmony Search (HS), Teaching Learning Based Optimization (TLBO), Cuttlefish Algorithm (CFA), and Emperor Penguin Optimizer (EPO)) to ensure the superiority of the newly proposed hybrid technique. The results display that the introduced TLBO-EO reduced the maximum overshoot by 30% and the steady-state error by 93% when compared to other techniques.
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