In the scope of solar energy-based electrical needs in rural tropical regions, the present article develops and confronts experimental power models from the using of manufacturer data and a new model made with the meteorological and electrical data acquired. These data are registered through an acquisition station around a monocrystalline photovoltaic panel, designed and realized in the scope of this work. After the acquisition of meteorological data, a choice of the most relevant meteorological variable as input vectors to express the output powers obtained was carried out. Around the Single-Diode model, seven models are performed with analytics equations, iterative methods and an optimization method with a multi-objective function to get internal parameters. The proposed experimental model is made by a combination of the solution got at STC of an iterative method, with the value of nameplate and the use of an open circuit voltage equation with experimental coefficient to predict power output in operating conditions, and it's demonstrated more efficient. The optimization of a multi-objective function using Nonlinear Squares (NLS) through the Leveng-Marqued method to solve the parameter estimation of a PV panel has been well done and the results are useful, like classic iterative method and less time-consuming.
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