制冷学报2026，Vol.47Issue(1)：71-79,9.DOI:10.12465/issn.0253-4339.20250808003
数据中心冷热一体化综合系统全年能碳特性及效率评价分析
Annual Energy-Carbon Characteristics and Efficiency Evaluation of an Integrated Cooling and Waste-Heat Recovery System in Data Centers
摘要
Abstract
Waste-heat recovery and utilization represent key technological pathways for promoting the low-carbon development of data centers.A comprehensive analysis of annual energy consumption and carbon emissions,coupled with a rational evaluation of system-level efficiency,is essential for advancing the integrated utilization of data-center resources.This study focuses on an integrated cooling and waste-heat recovery system in data centers and proposes two evaluation indicators from the perspectives of energy and carbon emissions:general exergy efficiency,ηGEX and general carbon efficiency,ηGOC.The proposed indicators are validated using simulation data.The results indicate that the general exergy efficiency metric effectively evaluates data center integrated systems.Specifically,the system in Lhasa achieves the highest general exergy efficiency of 29.27%,whereas the lowest general exergy efficiency(23.65%)is observed in Harbin.The general carbon efficiency indicator enables a quantitative assessment of the carbon-reduction potential achieved by replacing conventional heating systems integrated with data centers.Depending on the type of displaced traditional heating technology used,the general carbon efficiency in Lhasa ranges from 3.75 to 4.45.Overall,the proposed evaluation framework provides a robust and rational basis for assessing the operational efficiency and carbon-mitigation potential of data center integrated systems,offering valuable guidance for their practical deployment and retrofitting in modern data centers.关键词
数据中心/综合系统/余热回收/综合㶲效率/综合碳效率Key words
data center/integrated system/waste heat recovery/general exergy efficiency/general carbon efficiency分类
通用工业技术引用本文复制引用
周峰,田旭文,陈鸣飞,彭妍妍,姚克文,马国远..数据中心冷热一体化综合系统全年能碳特性及效率评价分析[J].制冷学报,2026,47(1):71-79,9.基金项目
国家自然科学基金(52478075)资助项目.(The project was supported by the National Natural Science Foundation of China(No.52478075).)本文受内蒙古重点研发和成果转化计划项目(2025YFHH0264)和工业和信息化部算力强基揭榜项目资助.(The project was supported by Inner Mongolia Key Research and Development and Scientific Achievement Transformation Project of China (No. 2025YFHH0264) and MIIT Computing Power Infrastructure Strengthening Challenge Projects of China. ) （52478075）
