摘要
针对数据中心存在的巨大能源消耗问题,研究分析了既有数据中心的用能特点,基于数据中心历史运行数据和现场实际情况,结合可视化监测、智能化调控、数字化管理技术,从运行、调控、管理多维度提出数据中心能效提升方案。以粤港澳大湾区某数据中心为例,说明能效提升方案实施的可行性和高效性。结果表明,制冷系统能效是影响数据中心用能效率的关键因素,其中冷水机组和末端设备用电是数据中心节能突破口。采用研究的能效提升方案后,案例数据中心平均能源利用效率(PUE)由1.416降低至1.305,平均制冷负载系数(CLF)由0.403降低至0.291,满足大湾区数据中心能效利用效率指标要求。制冷系统平均节能率27.61%,其中春季(1月-3月)节能率高达35.40%。2022年8月-2023年5月,数据中心已节省用电1764190 kW·h,减少二氧化碳排放2111 t,节省能源费用1757000元,项目投资回收期约4年。研究结果可为同类型数据中心能效提升提供技术参考,助力我国实现高质量数字化转型。
Addressing the significant energy consumption in internet data centers(IDCs),the energy usage characteristics of an existing IDC are analyzed.Based on historical operational data and on-site observations,integrated with techniques such as visual monitoring,intelligent control,and digital management,a multidimensional approach is proposed to enhance IDC energy efficiency across operation,control,and management aspects.Using an IDC in the Greater Bay Area of Guangdong,Hong Kong,and Macao as a case study,the feasibility and effectiveness of the efficiency enhancement scheme are demonstrated.Results indicate that the efficiency of cooling systems is crucial to overall energy efficiency,with particular emphasis on optimizing the energy usage of chillers and end devices for significant energy savings.Following implementation of the proposed efficiency enhancement measures,the case study IDC achieved an average Power Usage Effectiveness(PUE)reduction from 1.416 to 1.305 and an average Cooling Load Factor(CLF)reduction from 0.403 to 0.291,meeting the efficiency benchmarks for IDCs in the Greater Bay Area.The average energy savings rate of cooling systems reached 27.61%,with a peak of 35.40%during spring(January to March).From August 2022 to May 2023,the IDC saved 1764190 kW·h of electricity,reducing carbon dioxide emissions by 2111 metric tons and saving energy costs amounting to 1757000 yuan,with an estimated project payback period of about 4 years.The research outcomes provide technical insights for enhancing efficiency in similar IDCs,contributing to the high-quality digital transformation in China.
作者
黄晓斐
闫军威(指导)
周璇
申傲
杨志贤
HUANG Xiaofei;YAN Junwei;ZHOU Xuan;SHEN Ao;YANG Zhixian(School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510641,China;Guangdong Artificial Intelligence and Digital Economy Laboratory(Guangzhou),Guangzhou 510220,China)
出处
《建筑节能(中英文)》
2025年第10期1-11,共11页
Building Energy Efficiency
关键词
数据中心
能源利用效率
能效提升
智能化控制
制冷系统
data center
Power Usage Effectiveness(PUE)
energy efficiency improvement
intelligent control
cooling systems
