Parameter Identification for PV Modules Based on an Environment-Dependent Double-Diode Model

By Fabrício Bradaschia, Marcelo Cabral Cavalcanti, A. J. do Nascimento, Emerson Alves da Silva, Gustavo Medeiros de Souza Azevedo. IEEE Journal of Photovoltaics, 2019

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Most of the photovoltaic (PV) models involve mainly the reproduction of the nonlinear I–V curves for PV modules with a certain degree of accuracy. Previous researches have used equivalent circuits based on common electronic devices to model the real behavior of PV modules, such as the single and double diode models. Unfortunately, those models are static, i.e., they can reproduce the I–V curve of a PV module for a specific environmental condition (fixed irradiance and temperature). As consequence, different models should be obtained for each different environmental condition, restricting the use of the models for a limited set of irradiance and temperature values. The first contribution of this paper is the proposition of an irradiance and temperature dependent double-diode model for PV modules. In this model, the internal parameters depend on the environmental conditions, extrapolating its use for temperature and irradiance values different from those the parameters were initially estimated. In addition, two parameter estimation techniques are proposed for this new model. The techniques use a combination of analytical equations and numerical optimization based on the pattern search algorithm. Comparison results based on experimental I–V curves of real PV modules are presented in order to prove the accuracy of the model and techniques.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/b709cc31acc4a14587f74e3999285855629ab412