Factorial design and response surface optimization for modeling photovoltaic module parameters
In this paper, based on factorial design of experiments method (DoE), predictive model and surface response analysis methodology was used for studying, modeling, characterizing and optimizing the parameters of a mono-crystalline photovoltaic (PV) panel behavior considering the interactive effects of...
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doaj-5bf2cc14d79143e3bd2079a3730b96d02020-11-25T02:58:10ZengElsevierEnergy Reports2352-48472020-02-016299309Factorial design and response surface optimization for modeling photovoltaic module parametersFatma Zohra Kessaissia0Abdallah Zegaoui1Michel Aillerie2Mustapha Arab3Mohamed Boutoubat4Chahinez Fares5Department of Electrical Engineering. Hassiba Benbouali University, Chlef, Algeria; Laboratoire Matériaux Optiques, Photonique et Systèmes, LMOPS, EA 4423, Université de Lorraine, 57070 Metz, FranceDepartment of Electrical Engineering. Hassiba Benbouali University, Chlef, Algeria; Laboratoire Matériaux Optiques, Photonique et Systèmes, LMOPS, EA 4423, Université de Lorraine, 57070 Metz, FranceLaboratoire Matériaux Optiques, Photonique et Systèmes, LMOPS, EA 4423, Université de Lorraine, 57070 Metz, France; Laboratoire Matériaux Optiques, Photonique et Systèmes, LMOPS, CentraleSupelec, Université Paris-Saclay, 57070 Metz, France; Corresponding author at: Laboratoire Matériaux Optiques, Photonique et Systèmes, LMOPS, EA 4423, Université de Lorraine, 57070 Metz, France.Department of Electrical Engineering. Hassiba Benbouali University, Chlef, AlgeriaUniversity Amar Thlidji, Laghouat, AlgeriaDepartment of Electrical Engineering. Hassiba Benbouali University, Chlef, AlgeriaIn this paper, based on factorial design of experiments method (DoE), predictive model and surface response analysis methodology was used for studying, modeling, characterizing and optimizing the parameters of a mono-crystalline photovoltaic (PV) panel behavior considering the interactive effects of two variables surface PV cell temperature and solar irradiation levels. The DoE concept allows finding the predictive model of each parameter behavior that uses the experimental data. It enables accurate predictions of the responses according to input factors variations. This contribution evaluates the output parameters by predicting these mathematical models of the three responses of a mono-crystalline PV panel: the maximum power Pm, the short-circuit current Iscand the open circuit voltage Vocas function of the influences of both input parameter factors: illumination and temperature. In addition, to validate the results of the DoE predictive models, the surface response and the contour curves analysis were used to bring out the optimum of each response in each operating point covering the domain of the study by the use of a script developed under Minitab is deduced. The obtain results are compared with experimental data. Keywords: Factorial design of experiments method, Experimental design method, Predictive model, Surface response analysis, Photovoltaic modules, ANOVAhttp://www.sciencedirect.com/science/article/pii/S2352484719312235 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fatma Zohra Kessaissia Abdallah Zegaoui Michel Aillerie Mustapha Arab Mohamed Boutoubat Chahinez Fares |
spellingShingle |
Fatma Zohra Kessaissia Abdallah Zegaoui Michel Aillerie Mustapha Arab Mohamed Boutoubat Chahinez Fares Factorial design and response surface optimization for modeling photovoltaic module parameters Energy Reports |
author_facet |
Fatma Zohra Kessaissia Abdallah Zegaoui Michel Aillerie Mustapha Arab Mohamed Boutoubat Chahinez Fares |
author_sort |
Fatma Zohra Kessaissia |
title |
Factorial design and response surface optimization for modeling photovoltaic module parameters |
title_short |
Factorial design and response surface optimization for modeling photovoltaic module parameters |
title_full |
Factorial design and response surface optimization for modeling photovoltaic module parameters |
title_fullStr |
Factorial design and response surface optimization for modeling photovoltaic module parameters |
title_full_unstemmed |
Factorial design and response surface optimization for modeling photovoltaic module parameters |
title_sort |
factorial design and response surface optimization for modeling photovoltaic module parameters |
publisher |
Elsevier |
series |
Energy Reports |
issn |
2352-4847 |
publishDate |
2020-02-01 |
description |
In this paper, based on factorial design of experiments method (DoE), predictive model and surface response analysis methodology was used for studying, modeling, characterizing and optimizing the parameters of a mono-crystalline photovoltaic (PV) panel behavior considering the interactive effects of two variables surface PV cell temperature and solar irradiation levels. The DoE concept allows finding the predictive model of each parameter behavior that uses the experimental data. It enables accurate predictions of the responses according to input factors variations. This contribution evaluates the output parameters by predicting these mathematical models of the three responses of a mono-crystalline PV panel: the maximum power Pm, the short-circuit current Iscand the open circuit voltage Vocas function of the influences of both input parameter factors: illumination and temperature. In addition, to validate the results of the DoE predictive models, the surface response and the contour curves analysis were used to bring out the optimum of each response in each operating point covering the domain of the study by the use of a script developed under Minitab is deduced. The obtain results are compared with experimental data. Keywords: Factorial design of experiments method, Experimental design method, Predictive model, Surface response analysis, Photovoltaic modules, ANOVA |
url |
http://www.sciencedirect.com/science/article/pii/S2352484719312235 |
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