Two datasheet-based approaches for double-diode PV modeling with an efficient trade-off between accuracy and simplicity

A reliable photovoltaic (PV) model with logical trade-off between accuracy and simplicity can be utilized for optimal design, monitoring, fault detection and prediction of operational power. In this research work, two novel datasheet-based approaches are developed for PV module identification through double-diode model (DDM). In both methods the four unknown parameters are derived as functions of series resistance ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub><mml:mrow><mml:mi>R</mml:mi></mml:mrow> <mml:mrow><mml:mi>s</mml:mi></mml:mrow> </mml:msub> </mml:math> ). It is shown that each parameter estimation algorithm has its own unique solution. Effective numerical methods are applied for fast convergence and with absolute certainty to the corresponding unique solution. The established methods are both reasonably simple and accurate while one is simpler (faster) and the other is more accurate. The performances of the proposed algorithms are evaluated by real experimental data and through a comparison with other similar datasheet-based algorithms. The results reveal that the developed methods have superb performance in comparison with other techniques.