A comparison of the performance of a direct expansion solar assisted heat pump working with R22 and a mixture of R407C

Abstract

In the present work, an experimental investigation has been made of a direct expansion solar assisted heat pump (DXSAHP) working with R22 and mixture of R407C–liquefied petroleum gas (LPG). The experiments were carried out under the meteorological conditions of Calicut (latitude of 11.15 °N, longitude of 75.49 °E), India. An artificial neural network model with two neurons (ambient temperature and solar intensity) in input layer and five neurons (instantaneous compressor power consumption (PC), heating capacity, energy performance ratio (equivalent to coefficient of performance), compressor discharge temperature, and solar energy input ratio (SEIPR)) in the output layer has been developed for predicting the performance of a DXSAHP based on the data acquired from the experiments. The results showed that R407C–LPG (in the ratio of 70:30, by mass) has 1.2 per cent higher instantaneous compressor PC with 1–4.5 per cent lower heating capacity compared to R22. The energy performance ratio (EPR) of the mixture was found to be lower in the range of 2–5 per cent compared to that of R22. The compressor discharge temperature was also found to be low by 2 °C compared to R22. The SEIPR of the new mixture was found to be higher than that of R22 in the range of 7–14 per cent. Total equivalent warming impact of new refrigerant mixture was found to be low compared to R22 under leakage conditions. The results confirmed that R407C–LPG is an ozone friendly alternative option to phase out R22 in solar assisted heat pump applications.

Keywords

direct expansion solar assisted heat pump R22 R407C–liquefied petroleum gas alternative refrigerants artificial neural network

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A comparison of the performance of a direct expansion solar assisted heat pump working with R22 and a mixture of R407C–liquefied petroleum gas

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