A linear method to extract diode model parameters of solar panels from a single I–V curve

Lim, L. H. I., Ye, Z., Ye, J., Yang, D. and Du, H. (2014) A linear method to extract diode model parameters of solar panels from a single I–V curve. Renewable Energy, 76, pp. 135-142. (doi:10.1016/j.renene.2014.11.018)

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Abstract

The I-V characteristic curve is very important for solar cells/modules being a direct indicator of performance. But the reverse derivation of the diode model parameters from the I-V curve is a big challenge due to the strong nonlinear relationship between the model parameters. It seems impossible to solve such a nonlinear problem accurately using linear identification methods, which is proved wrong in this paper. By changing the viewpoint from conventional static curve fitting to dynamic system identification, the integral-based linear least square identification method is proposed to extract all diode model parameters simultaneously from a single I-V curve. No iterative searching or approximation is required in the proposed method. Examples illustrating the accuracy and effectiveness of the proposed method, as compared to the existing approaches, are presented in this paper. The possibility of real-time monitoring of model parameters versus environmental factors (irradiance and/or temperatures) is also discussed.

Item Type:Articles
Additional Information:NOTICE: this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy,76:135-142 (2015)] DOI: 10.1016/j.renene.2014.11.018
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Lim, Dr Li Hong Idris
Authors: Lim, L. H. I., Ye, Z., Ye, J., Yang, D., and Du, H.
Subjects:Q Science > Q Science (General)
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Journal Name:Renewable Energy
Publisher:Elsevier Ltd.
ISSN:0960-1481
ISSN (Online):1879-0682
Copyright Holders:Copyright © 2014 Elsevier Ltd.
First Published:First published in Renewable Energy 76:135-142
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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