Performance prediction of solid desiccant – Vapor compression hybrid air-conditioning system using artificial neural network

D.B. Jani, Manish Mishra and P.K. Sahoo

Energy, 2016, vol. 103, issue C, 618-629

Abstract: In the present study, ANN (artificial neural network) model for a solid desiccant – vapor compression hybrid air-conditioning system is developed to predict the cooling capacity, power input and COP (coefficient of performance) of the system. This paper also describes the experimental test set up for collecting the required experimental test data. The experimental measurements are taken at steady state conditions while varying the input parameters like air stream flow rates and regeneration temperature. Most of the experimental test data (80%) are used for training the ANN model while remaining (20%) are used for the testing of ANN model. The outputs predicted from the ANN model have a high coefficient of correlation (R > 0.988) in predicting the system performance. The results show that the ANN model can be applied successfully and can provide high accuracy and reliability for predicting the performance of the hybrid desiccant cooling systems.

Keywords: ANN; COP; Desiccant cooling; Hybrid system; Regeneration (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:103:y:2016:i:c:p:618-629

DOI: 10.1016/j.energy.2016.03.014

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