Refined photovoltaic parameters estimation via an improved Sinh Cosh Optimizer with trigonometric operators

Estimating parameters in solar cell models is crucial for simulating and designing photovoltaic systems. The single-diode, double-diode, and three-diode models represent these systems. Parameter estimation can be viewed as an optimization problem to minimize the difference between measured and estimated data. This study presents PV parameter estimation using the enhanced Sinh Cosh Optimizer (I_SCHO), incorporating trigonometric operators from the Sine Cosine Algorithm (SCA). This integration improves the algorithm's ability to navigate complex search spaces, avoid local optima, and expedite convergence. Assessment criteria include runtime, convergence behaviour, minimum RMSE, and system reliability measured by SD. Results show that I_SCHO consistently delivers superior accuracy and reliability compared to other methods. Experiments were conducted on five solar cells: RTC France, Photowatt-PWP201, Kyocera KC200GT, Ultra 85-P, and STM6-40/36 module. The study also includes a comparative analysis using state-of-the-art algorithms, demonstrating I_SCHO's efficiency through RMSE, Power Voltage (P-V) and Current Voltage (I-V) curves.