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In the recent era, Metaheuristic Algorithms (MHs) are developed to tackle many and different optimization problems. The merit of the MHs is not only its simplicity to understand but also its easiness of implementation which helps in tackling different and various real-world applications. Honey Badger Algorithm (HBA) is one of the recent MHs. Although the success of the HBA algorithm in solving complex problems with high dimensions, it suffers from several drawbacks such as; 1) being trapped in local optima issue, 2) low convergence, and 3) the imbalance between exploration and exploitation stages. Therefore, an efficient local search called Dimensional Learning Hunting (DLH) is injected to the HBA to tackle these drawbacks, the proposed method named mHBA. On the other side, the demand of the PV systems (PVSs)’ installations is rapidly increasing from a day to the next. Due to the intermittency of the weather …