Akademik Veri Yönetim Sistemi
Jordan Journal of Applied Science - Natural Science Series, cilt.18, sa.1, ss.24-29, 2024 (Hakemli Dergi)
Background: One of the greatest solutions that has been suggested to meet the growing global need for renewable energy is the efficient utilization of photovoltaic (PV) systems. Metaheuristic algo-rithms are frequently chosen over other approaches in the literature for parameter assessment of PV cells and modules due to their reliability and speed. Methods: For parameter determination of the STM6-40/36 PV module, this study proposes the h-ASPSO algorithm, a hybrid of particle swarm optimization (PSO) and atom search optimization (ASO) methods. Results: After several rounds of optimization using h-ASPSO, the objective function for root mean square error (RMSE) was found as 0.0017298. The strength and promise of h-ASPSO in identifying unknown PV model parameters are validated by the excellent agreement between the predicted and observed current and power measurements. Additionally, five metaheuristic algorithms from the literature were compared to h-ASPSO's statistical performance, confirming the suggested method's superiority. Conclusion and Implications: The research highlights h-ASPSO's potential as a reliable optimiza-tion tool, contributing to the advancement of renewable energy technologies and their integration into the energy landscape.