基于仿真的数据中心热效率优化方法

K. Fouladi, J. Schaadt
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引用次数: 0

摘要

在使用中央系统的数据中心中,冷却电子设备的能源消耗是巨大的,并且将继续上升。本研究的动机是基于需要确定优化策略,以使用基于模拟的方法来提高和优化数据中心的热效率。在这里,模拟用于建模和优化拟议的研究数据中心,以作为测试设备和研究最佳实践和策略(如密封和混合冷却)的环境。本研究中使用的优化技术在满足特定热一致性标准的同时,找到数据中心的最佳运行条件和遏制策略。更具体地说,在不同的密封配置下,包括在全部和部分设置下的热通道和冷通道密封策略,寻求冷却单元的最佳供应气流速率和温度设定值。计算流体动力学(CFD)模拟结果表明,在较低的送风气流速率和较高的送风温度设定值下,采用全热通道密封策略的数据中心出现热点的概率较低。优化方法有助于确定一个更有效的冷却系统,而不会有供应不足的风险。研究考虑了静态热负荷和固定设备布置的稳态条件。但是,在本研究中发展的一般优化过程应增加目前用于优化新的风冷数据中心的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Simulation-Based Approach to Data Center Thermal Efficiency Optimization
The energy consumption for cooling electronic equipment in data centers using central systems is significant and will continue to rise. The motivation of the present research study is based on the need to determine optimization strategies to improve and optimize the thermal efficiency of data centers using a simulation-based approach. Here, simulation is used to model and optimize a proposed research data center for use as an environment to test equipment and investigate best practices and strategies such as containment and hybrid cooling. The optimization technique used in this study finds the optimal operating conditions and containment strategies of the data center while meeting specific thermal conformance criteria. More specifically, optimum supply airflow rate and temperature setpoint of cooling units are sought under different containment configurations, including both hot aisle and cold aisle containment strategies in both full and partial setups. The results of the computational fluid dynamics (CFD) simulations indicated a lower probability of hot spots with full hot aisle containment strategy in a data center operating at lower supply airflow rate and higher supply temperature setpoint. The optimization approach helped to determine a more efficient cooling system without the risk of under-provisioning. The study considered steady-state conditions with static heat load and fixed equipment layout. However, the generalized optimization process developed in the present study should add to the repertoire of tools presently used for the optimization of new air-cooled data centers.
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