Archimedes optimization algorithm based parameter extraction of photovoltaic models on a decent basis for novel accurate RMSE calculation - Hussain, Md Tahmid; Hussan, Md Reyaz; Tariq, Mohd; Sarwar, Adil; Ahmad, Shafiq; Poshtan, Majid; Mahmoud, Haitham A. (Frontiers in Energy Research, 2024)
Solar PV has proved to be a viable alternative to the conventional fossil fuel-based generation system. It offers the advantage of pollution and maintenance free power production. It is important to understand the process of power generation and consequently modelling the power from solar PV in order to use it effectively. Manufacturers of solar panels do not provide the necessary parameter information for modelling the cells/panels for study purpose. The aim of this research is to use an optimization technique namely Archimedes Optimization Algorithm (AOA) to determine the unknown solar PV parameters for PVM752 GaAs thin film solar cell and the RTC France solar cell. In this work, a Single Diode Model (SDM) and a Double Diode Model (DDM) has been used to model the solar cells. The performances are evaluated using the well-known sum of individual absolute errors (SIAE) and a novel root mean square error (RMSE) method. The effectiveness of the suggested algorithm is evaluated alongside that of a variety of other optimization methods. The RMSEs using equation ( 18) for the AOA applied to the SDM and DDM of RTC France solar cell were 3.7415 × 10 -3 and 1.0033 × 10 -3 . Similarly, for PVM752 GaAs thin film solar cell were 1.6564 × 10 -3 , and 0.00106365, respectively. Likewise, the SIAE for both the solar diode models of RTC France cells were 0.071845 and 0.021268, respectively. For the PVM752 GaAs thin film, the corresponding SIAE values were 0.031488 and 0.040224. The results indicate that the AOA-based approach demonstrates efficient processing with consistent convergence, maintaining a high level of accuracy in the obtained solutions, and the suggested approach produces better results with a lower RMSE than other algorithms do.