Abstract

Air-source heat pump (ASHP) is wide used for its carbon neutrality. In cold climates, to ensure good efficiency and stability, cascade ASHP is a promising technology for high-temperature water application, such as space heating boilers retrofit. Cascade heat exchanger is a key component in cascade ASHP. However, there are few experimental studies on the effects of its area on system energetic, economic, and environmental performance under low ambient temperature and high water-supply temperature, which is essential for system improvement and application. Focusing on this research gap, this paper carries out experiment of cascade ASHP system performance and conducts analysis on system suitability based on recurrent Neural Network. To fairly compare system performance in different cold climate cities with different cascade heat exchanger areas, conversion factor γ is proposed and used in the analysis. The results show total energy consumption of compressors decreases the most in New York (21498 MJ) and least in Shenyang (9414 MJ) as cascade heat exchanger areas increases from 0.6 to 1.6 m2. Similarly, the system in New York shows the most significant reductions in carbon emissions (2701 kg/year) and total annual cost (225$), while that in Shenyang shows the smallest drop of 1277 kg/year and 118$, indicating it’s more meaningful to increase cascade heat exchanger area in a city with longer heating period. The results also show the COP varies significantly across cities, strongly correlated with average ambient temperature. The increase in COP slows down when cascade heat exchanger area reaches 1.6 m2, indicating even larger area is not recommended. These findings provide a foundation for improving and applying cascade ASHP in cold climates.

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