OICC Press International Journal of Energy and Environmental Engineering 2251-6832 14 3 (September 2023) 2022 09 13 Parameters identification for photovoltaic system via improved electromagnetism-like approach and quadrature technique 10.1007/s40095-022-00523-3 EN Ola Ragb Department of Engineering Mathematics and Physics, Faculty of Engineering, Zagazig University, Zagazig, EG Hanan Bakr Department of Engineering Mathematics and Physics, Faculty of Engineering, Zagazig University, Zagazig, EG O. Civalek Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, TW Journal Article 2022 09 13 Abstract Mathematical modelling of photovoltaic modules is substantial for performance analysis of PV cell. So, improved electromagnetism-like algorithm and differential quadrature approach are implemented to evaluate the parameters of photovoltaic single-, double- and three-diode model. Three tested cases are investigated on various PV systems like Kyocera polycrystalline (KC200GT), polycrystalline (Solarex MSX-60) and monocrystalline (R.T.C France). A MATLAB code is designed to solve this problem. The validity of the presented algorithms is explained by comparison of the computed results with other studied methods and calculating various statistical errors. Also, the results are verified by 10 different experimental I–V sets under various meteorological conditions for every panel. It’s found that the solutions of the presented approaches show high convergence speed and accuracy compared with different results where the standard deviation of the root mean square error reached 4.31E−4 A between calculated results and experimental measured data and achieved less CPU execution time 1.269 s for R.T.C France. Furthermore, various changed conditions including cell temperature and irradiance conditions are used to validate each method. Also, we compute the maximum power point to get the efficiency of each solar cell where PDQM achieves the best value of efficiency as 16.564 and fill factor = 74.5103 with CPU time = 0.520 s for KC200GT solar panel. Calculation solutions display that the presented techniques can obtain higher parameters identification precision.