Electromagnetism-Like Algorithm-Based Parameters Estimation of Double-Diode PV-Module Model

Abstract

Abstract An accurate parameters extraction of photovoltaic (PV) module is necessary as it plays an essential role in determining the performance of PV system. Therefore, an electromagnetism-like algorithm (EMLA) is proposed to optimally estimate associated parameters of double-diode PV module model. The parameters are optimized based on a proposed fitness function, which depends on the root mean square error between the experimental and computed PV output current. Seven different experimental data sets of I-V curve are utilized to verify the presented approach under various operation conditions. The results show there is a high fitness between the estimated and realistic I-V curves under different weather conditions. Furthermore, the results are validated with another model that proposed in literature under different statistical indices. Finally, the proposed PV modeling method exhibits under all operation conditions an average root mean square error, average mean bias error and average determination coefficient under all operation conditions were 0.0799, 0.0088, and 0.9863, respectively.