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This paper proposes a new approach based on Lambert W-function to extract the electrical parameters of photovoltaic (PV) panels. This approach can extract the optimal electrical characteristics of the PV panel under variable conditions of irradiation and temperature. Three benchmarking panels (shell SP70 monocrystalline silicon, shell ST40 thin film, and KC200GT Polycrystalline Silicon) are demonstrated and analyzed considering the electrical characteristics provided by the manufacturers. A comprehensive assessment is carried out under different weather condition to validate the capability and the robustness of the proposed approach. Furthermore, the simulated output characteristics of the three modules Photovoltaic are almost comparable and reproduce faithfully the manufacturer’s experimental data The novelty of this study is the using a new hybrid analytical and numerical method that straight forward and effective given value of Root mean square error less than those obtained by others methods that indicate the estimated results are very close to the experimental values provided by the manufacturers.

Today, photovoltaic (PV) panels represent a large part of total power generation. Photovoltaic cells and modules parameter estimation is a relevant field of research that plays a critical role in PV system modeling and simulation. This paper presents a new simple and accurate hybrid method to estimate the five parameters of the single-diode model. The proposed method aims to build a set of equations as functions of the five unknown parameters based on the three remarkable points and the PV datasheet's information. These equations will be used to derive a closed form expression for I0, Iph, Rsh, and Rs. This paper also presents a new simple iterative approach to better estimate the fifth parameter, the ideality factor (n), using only datasheet information. The novelty of this study is to use a new effective simple hybrid method that combines the analytical and the iterative approaches based on the increment of the ideality factor by step of 0.01Vt to achieve the minimum Root Mean Square Error possible. The results reveal that the proposed method outperforms a large number of analytical, numerical, and even the most powerful meta-heuristic algorithms in terms of accuracy, simplicity and reliability.