Optimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithm

The paper proposes an enhanced moth search algorithm (EMSA) employed in identifying the optimal parameters of Triple-Junction (TJS) photovoltaic panel under different operating conditions. Disruptor operator (DO) is placed in the moth search algorithm (MSA) to improve its performance. The DO is used to improve the diversity of the MSA and avoid it from stuck in local point. The presented fitness function in this work is the integral time absolute error (ITAE) between the triple junction PV panel experimental and calculated currents. The panel is simulated in Simulink and tested under different solar radiation conditions. Additionally, the panel performance is investigated under the shadow effect; a comparative study is performed with other metaheuristic optimization approaches and with Hammerstein and wiener identification technique. The proposed EMSA operates with efficiencies around 99.66% and 99.89%for first and second patterns respectively. It is confirmed the superiority and reliability of the proposed EMSA in extracting the optimal parameters of TJS based module operated at different operating conditions.