气候变化领域集成服务门户(CCPortal): Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis

CCPortal

DOI	10.1016/j.energy.2020.119232
	Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis
	Xu Y.; Mao C.; Huang Y.; Shen X.; Xu X.; Chen G.
发表日期	2021
ISSN	3605442
卷号	216
英文摘要	For the advantages of high efficiency and low impact to the environment, CO2 air source heat pump water heater (ASHPWH) is applied to produce domestic water, which also reveals good potential in cold regions. In order to boost the system performance and practicability under low ambient temperature, optimization for CO2 ASHPWH is conducted using non-dominated sorting genetic algorithm (NSGA-II). A validated artificial neural network (ANN) predicts energy parameters for the optimization. And an economic model provides economic and environmental parameters, which considers the influence of housing price, tank volume, and on/off-peak electricity price, rarely taken into account in published studies. Then the optimizing progress is conducted under −20 °C ambient temperature and 9–65 °C water temperature, in which four optimized variables are selected: gas cooler outlet temperature (Tgc), heat rejection pressure (Pgc), compressor displacement (qvh) and water tank volume (Vwt). The final solution of Tgc = 15 °C, Pgc = 8294.1 kPa, Vwt = 0.3647 m3, qvh = 401.33 mL/s results in two objectives (CO2 emission and total annual cost) of 8599.4 kg and 1626.9 $/year, revealing advantages both in energy and economy. It is noteworthy that the cost of the space occupied by system is the fourth important factor in capital cost. These results lay solid foundation for further studies and system application. © 2020 Elsevier Ltd
英文关键词	Air-source heat pump; Artificial neural network; CO2; Low-temperature; Multi-objective optimization
scopus关键词	Air source heat pumps; Carbon dioxide; Economic analysis; Genetic algorithms; Hot water distribution systems; Housing; Multiobjective optimization; Solar water heaters; Temperature; Water heaters; Water tanks; Air source heat pump water heaters; Electricity prices; Environmental parameter; Heat pump water heater; Low ambient temperatures; Non dominated sorting genetic algorithm (NSGA II); System applications; Water temperatures; Neural networks; artificial neural network; carbon dioxide; displacement; economic analysis; energy efficiency; equipment; genetic algorithm; low temperature; optimization; performance assessment; temperature effect
来源期刊	Energy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/177259
作者单位	Engineering Research Center of Process Equipment and Remanufacturing, Ministry of Education, College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, 310014, China; Zhejiang Zhenglishengneng Sci-Tech Ltd, Wenzhou, 325600, China; Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Chongqing University, Chongqing, 400044, China; Key Laboratory of Refrigeration and Cryogenic Technology of Zhejiang Province, Institute of Refrigeration and Cryogenics, Zhejiang University, Hangzhou, 310000, China
推荐引用方式 GB/T 7714	Xu Y.,Mao C.,Huang Y.,et al. Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis[J],2021,216.
APA	Xu Y.,Mao C.,Huang Y.,Shen X.,Xu X.,&Chen G..(2021).Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis.Energy,216.
MLA	Xu Y.,et al."Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis".Energy 216(2021).