Photovoltaic (PV) parameter estimation of a multicrystalline panel using developed iterative and non-iterative methods

Mathematical modeling of photovoltaic (PV) modules is essential for any performance optimization operation or diagnostic of the photovoltaic generator under changing environmental conditions. The limited data available are provided by commercial manufacturing datasheets. The accurately estimating of...

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Bibliographic Details
Main Authors: Obbadi, Abdellatif, Errami, Youssef, Elfajri, Abdelkrim, Agunaou, Mustapha, Benhmida, Mohammadi, Sahnoun, Smail
Format: Conference Proceeding
Language:English
Subjects:
Estimating
Iterative methods
Mathematical models
Matlab
Modules
Photovoltaic cells
Solar cells
Tracking
Online Access:Get full text
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Summary:Mathematical modeling of photovoltaic (PV) modules is essential for any performance optimization operation or diagnostic of the photovoltaic generator under changing environmental conditions. The limited data available are provided by commercial manufacturing datasheets. The accurately estimating of these parameters remains a challenge for researchers. There is great diversity in the models and the estimation methods i.e., iterative and non-iterative methods. In this paper we are interested in estimating the parameters of both complete (5-parameter) and simplified (4-parameter) single-diode PV models by non-iterative and iterative methods i.e., the Newton-Raphson and Halley's method. The aim is to predict the behavior of a multicrystalline Kyocera KC200GT module under real environmental conditions. A new parameter Series/Parallel Ratio (SPR) ranking photovoltaic modules is defined. Depending on the value SPR, we can neglect the series or shunt resistance of single-diode model without compromising accuracy. The proposed approach is a quick and non-iterative method that allows the estimation of PV parameters. It can be used in tracking applications of Maximum Power Point Tracking (MPPT) for on-line. The results obtained with non-iterative and iterative methods are compared with experimental data. The results are discussed in terms of precision and order statistical errors. They show the limits of the use of these approaches and their relevance. The method is verified by the simulation using MATLAB/Simulink environment.
ISSN:2380-7393
DOI:10.1109/IRSEC.2015.7455009