Predicting the performance of solar photovoltaic thermal Water Collectors using hybrid fuzzy logic expert system

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 differen...

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Bibliographic Details
Published in:International journal of ambient energy 2022-12, Vol.43 (1), p.8098-8112
Main Authors: Sridharan, M., Prakash, B.
Format: Article
Language:English
Subjects:
fuzzy
Hybrid
prediction
PV/T
solar
system
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Summary: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 of an overall prediction accuracy of 95.50%. Also, the prediction accuracy of this H-M-FLES is 0.52% higher than that of the available FLES based literature.
ISSN:0143-0750
2162-8246
DOI:10.1080/01430750.2022.2086913