A Fractional Order-Kepler Optimization Algorithm (FO-KOA) for single and double-diode parameters PV cell extraction

• DOI: 10.1016/j.heliyon.2024.e35771
• Publication Date: 2024-08-05T18:29:50Z
• Authors: Sultan Hassan Hakmi; Hashim Alnami; Ahmed Ginidi; Abdullah Shaheen; Thamer A.H. Alghamdi
• Keywords: Robustness; Premature convergence

The primary objective of this study is to investigate the effects Fractional Order Kepler Optimization Algorithm (FO-KOA) on photovoltaic (PV) module feature identification in solar systems. Leveraging strengths original KOA, FO-KOA introduces fractional order elements and a Local Escaping Approach (LEA) enhance search efficiency prevent premature convergence. FO element provides effective information past expertise sharing amongst participants avoid converging. Additionally, LEA incorporated boost procedure by evading local optimization. single-diode-model (SDM) Double-diode-model (DDM) are two different equivalent circuits that used for obtaining unidentified parameters PV. Applied KC-200, Ultra-Power-85, SP-70 PV modules, compared KOA technique contemporary algorithms. Simulation results demonstrate FO-KOA's remarkable average improvement rates, showcasing its significant advantages robustness over earlier reported methods. proposed demonstrates exceptional performance, outperforming existing algorithms 94.42 %–99.73 % optimizing cell parameter extraction, particularly KC200GT module, consistent superiority robustness. Also, validated SDM DDM well-known RTC France cell.