An improved single-diode model parameters extraction at different operating conditions with a view to modeling a photovoltaic generator: A comparative study

Abstract This paper proposes advanced analytical, numerical and genetic algorithm (GA) approaches for retrieving the parameters of photovoltaic (PV) panel. A comparative study for extracting the five parameters of a single diode PV model is presented. Based on the datasheet values, a numerical based Newton-Raphson algorithm is investigated for solving the current-voltage relation of a single diode solar PV model. To highlight the rigorous performance of our models, a second analytical model is proposed. For improving the accuracy of solar panel parameters, a technique based on GA is established. This approach is based on the problem of research and optimization of the extracted parameters as an objective function. To account for variation in solar radiation and temperature, these models are presented under the reference and real operating conditions. The performances of the proposed algorithms are compared by using MATLAB scripts programming, and the theoretical advantages of GA model were demonstrated. The different models are validated experimentally by various tests of temperature and solar irradiance variation. The experimental results indicate that the GA model has a very satisfactory performance compared with the two other models and it offers good compromise between accuracy and fastness.