Factorial design and response surface optimization for modeling photovoltaic module parameters

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 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