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Bonanno, F., Capizzi, G., Graditi, G., Napoli, C. and Tina, G.M. (2012) A Radial Basis Function Neural Network Based Approach for the Electrical Characteristics Estimation of Aphotovoltaic Module. Applied Energy, 97, 956-961. http://dx.doi.org/10.1016/j.apenergy.2011.12.085

has been cited by the following article:

• TITLE: Fuzzy Estimation Analysis of Photovoltaic Model Parameters

  AUTHORS: Helal Al-Hamadi

  KEYWORDS: Photovoltaic Cell, Parameter Sensitivity, Fuzzy Logic, Diode Model, Modeling

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.3 No.7, July 17, 2015

  ABSTRACT: One of the challenges in accurately estimating Photovoltaic (PV) cell electric performance is the uncertainty of the model equivalent circuit parameters. The parameters considered in the study are the series resistance, shunt resistance, photo current, saturation current, and diode ideality factor. Parameter estimation for the PV cell equivalent circuit model is challenging due to the implicit transcendental relationship of the I-V characteristics of the cell. This paper presents a fuzzy logic based study for estimating the uncertainty of the cell parameters. The model parameters change with temperature and irradiance, are the source of uncertainties. Mathematical programming is used to estimate the fuzzy parameters. The approach is performed on practical data and the results of the analysis provide the estimation of the PV cell parameters. Results of this research yielding better estimated parameters compared with other methods using the Absolute Mean Error (AME).