Verification and Validation of Solar Photovoltaic Thermal Water Collectors Performance Using Fuzzy Logic

Abstract

The performance of the solar photovoltaic (PV) module is more sensitive to its operating temperature. A PV module with a cooling system produces higher electrical power output than a PV module without a cooling system. In addition, the PV module with the integrated cooling system is capable of generating electrical and thermal energy simultaneously. Such an integrated (hybrid) system is termed as a solar photovoltaic thermal (PV/T) system. When two or more collectors connected in series as a mean to have higher output, then such a system is termed as series-connected PV/T water collectors. This study presents two fuzzy inference systems (FISs), namely, Mamdani and Sugeno, for predicting the performance of series-connected PV/T water collectors. The set of rules was framed individually for both models in a way to predict the power output of PV/T water collectors in an inaccurate manner. The predicted results by inference systems are compared with experimental values to check their prediction accuracies. The accuracy of such a proposed Mamdani and Sugeno FIS is 95.67% and 99.92%.