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Silicon PV module fitting equations based on experimental measurements

Mathematical models; Mean square error; Nonlinear equations; Photovoltaic cells; Silicon; Solar power generation; Characteristic curve; Evaluation parameters; I - V curve; Mathematical formulas; Measurement based model; Nonlinear activation functions; Root mean squared errors; Solar photovoltaics; C...

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Main Authors: Sabry A.H., Hasan W.Z.W., Sabri Y.H., Ab-Kadir M.Z.A.
Other Authors: 56602511900
Format: Article
Published: John Wiley and Sons Ltd 2023
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id my.uniten.dspace-24799
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spelling my.uniten.dspace-247992023-05-29T15:27:15Z Silicon PV module fitting equations based on experimental measurements Sabry A.H. Hasan W.Z.W. Sabri Y.H. Ab-Kadir M.Z.A. 56602511900 57219410727 57202008988 25947297000 Mathematical models; Mean square error; Nonlinear equations; Photovoltaic cells; Silicon; Solar power generation; Characteristic curve; Evaluation parameters; I - V curve; Mathematical formulas; Measurement based model; Nonlinear activation functions; Root mean squared errors; Solar photovoltaics; Curve fitting Solar photovoltaic (PV) characteristic curves (P-V and I-V) offer the information required to configure the PV system to operate as near to its optimal performance as possible. Measurement-based modeling can provide an accurate description for this purpose. This work analyzes the PV module performance and develops a mathematical formula under particular weather conditions to accurately express these curves based on a custom neural network (CNN). The study initially presents several standard mathematical model equations, such as polynomial, exponential, and Gaussian models to fit the PV module measurements. The model selection is subjected to the minimum value of an evaluation parameter. To simplify the solution of the symbolic equations for the CNN network, two neurons in the hidden layer with nonlinear activation function and linear for the output layer were selected. The results show the effectiveness of the proposed CNN model equations over other standard fitting models according to the root mean squared error (RMSE) evaluation. This method promises further improved results with multi-input parameter modeling. � 2018 The Authors. Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd. Final 2023-05-29T07:27:15Z 2023-05-29T07:27:15Z 2019 Article 10.1002/ese3.264 2-s2.0-85062024055 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062024055&doi=10.1002%2fese3.264&partnerID=40&md5=f3f10bdc02b751b8ddbc86a398478589 https://irepository.uniten.edu.my/handle/123456789/24799 7 1 132 145 All Open Access, Gold, Green John Wiley and Sons Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Mathematical models; Mean square error; Nonlinear equations; Photovoltaic cells; Silicon; Solar power generation; Characteristic curve; Evaluation parameters; I - V curve; Mathematical formulas; Measurement based model; Nonlinear activation functions; Root mean squared errors; Solar photovoltaics; Curve fitting
author2 56602511900
author_facet 56602511900
Sabry A.H.
Hasan W.Z.W.
Sabri Y.H.
Ab-Kadir M.Z.A.
format Article
author Sabry A.H.
Hasan W.Z.W.
Sabri Y.H.
Ab-Kadir M.Z.A.
spellingShingle Sabry A.H.
Hasan W.Z.W.
Sabri Y.H.
Ab-Kadir M.Z.A.
Silicon PV module fitting equations based on experimental measurements
author_sort Sabry A.H.
title Silicon PV module fitting equations based on experimental measurements
title_short Silicon PV module fitting equations based on experimental measurements
title_full Silicon PV module fitting equations based on experimental measurements
title_fullStr Silicon PV module fitting equations based on experimental measurements
title_full_unstemmed Silicon PV module fitting equations based on experimental measurements
title_sort silicon pv module fitting equations based on experimental measurements
publisher John Wiley and Sons Ltd
publishDate 2023
_version_ 1806426211721674752
score 13.214268

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