Parametric study of design factors on the performance of flexible solar modules

Abstract

ABSTRACT Solar cells have traditionally been built on rigid substrates. However, a lot of research is currently going on to improve the design and performance of solar cells built on flexible substrates. Flexible solar cells are light and rugged; however, the cell’s efficiency is highly affected by factors related to the design or the environment. In many instances, the effect of one factor on the performance of solar modules is affected by the levels of other factors. Therefore, in this work, analysis of variance (ANOVA) tools were used to study the simultaneous effect of design factors of shading, air gap, and curvature on the performance of flexible solar modules. Furthermore, an artificial neural network used the experimental data to predict the performance of the modules under similar conditions. The ANOVA results showed that all the main factors were significant and directly influenced the performance of the solar module. Furthermore, the combined effect of the factors is also significant. Furthermore, the ANN model was able to predict the performance of the modules with high precision, as indicated by the coefficient of determination (R2) value of 99.92%.