Seasonal heating performance prediction of air-to-water heat pumps based on short-term dynamic monitoring

Xiaoyu Sun, Zhichao Wang, Xiaofeng Li, Zhaowei Xu, Qiang Yang and Yingxia Yang

Renewable Energy, 2021, vol. 180, issue C, 829-837

Abstract: Air-to-water heat pumps (AWHPs) utilize renewable energy and have found worldwide applications, with the seasonal coefficient of performance (SCOP) as a key index. Considering reliability and costs, short-term dynamic monitoring combined with regression analysis and extrapolation is used for predicting SCOP. Different regression models are being researched. A statistical analysis method is proposed to work out the optimal scheme. A series of prediction models with different independent variables, fitting methods and training dataset acquisition methods are discussed. Two indicators, the qualification rate R±10% and the maximum relative error Emax, are proposed for accuracy evaluation. For analysis a typical AWHP heating system in Beijing was monitored for 78d. Linear fitting performs better than quadratic polynomial fitting. For the consecutive-day method, the prediction deviation decreases with a longer test time and presents diminishing marginal benefits. A critical value of 10-day is identified and unrepresentative days should be avoided. For the typical-meteorological-day method, three days with an outdoor air temperature (Tout) range covering over 50% days of the heating season and including the average Tout of local winter are recommended. Satisfactory prediction results are realized, with R±10%>97% and Emax<14%, while using Tout or the difference between water temperature and Tout presents consistent accuracy.

Keywords: Air-to-water heat pump; Seasonal performance; Field trial; Statistical analysis; Performance extrapolation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:180:y:2021:i:c:p:829-837

DOI: 10.1016/j.renene.2021.08.130

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