Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244000 
Year of Publication: 
2020
Citation: 
[Journal:] Energy Reports [ISSN:] 2352-4847 [Volume:] 6 [Issue:] 3 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2020 [Pages:] 299-309
Publisher: 
Elsevier, Amsterdam
Abstract: 
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 , the short-circuit current and the open circuit voltage as 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.
Subjects: 
Factorial design of experiments method
Experimental design method
Predictive model
Surface response analysis
Photovoltaicmodules
ANOV
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article
Appears in Collections:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.