Predicting the Performance of Solar Photovoltaic Thermal Water Collectors Using Hybrid Fuzzy Logic Expert System

Abstract

ABSTRACT This study presents a hybrid Mamdani fuzzy logic expert system (H-M-FLES), which predicts the overall performance delivered by three differently connected solar photovoltaic thermal water collector systems (S-PV/T-W-C-S). For training the FLES, real-time experiments are conducted with three differently connected S-PV/T-W-C-S (stand-alone, series and parallel) test rigs at Tiruchirappalli, India. Then, the trained model was tested and validated against the real-time experimental results. The results predicted by this newly proposed H-M-FLES is in-line with the experimental results with the overall prediction accuracy of 95.50%. Also, the prediction accuracy by this H-M-FLES is 0.52% higher than that of the available FLES based literature.