基于模型预测控制的模块化数据中心ICT设备使用冷却控制对扰动的抑制作用

M. Ogawa, Hiroshi Endo, Hiroyuki Fukuda, H. Kodama, Toshio Sugimoto, H. Soneda, Masao Kondo
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引用次数: 6

摘要

针对模块化数据中心,提出了一种基于模型预测控制(MPC)的冷却控制方法,以降低由于信息通信技术(ICT)设备利用率波动而导致的CPU温度峰值。为了应对波动,提出的方法不仅使用预测模型考虑服务器功耗,而且根据服务器功耗的上升速率在MPC控制器和必要风量控制器之间切换。MPC控制器控制CPU温度是为了同时做三件事:避免抑制CPU的运行,尽可能减少数据中心冷却风扇消耗的功率,并调整波动的影响。必要风量控制器计算冷却风扇转速的命令值,以在最大CPU利用率期间提供所需的风量。控制仿真结果表明,所提出的控制方法可以显著降低CPU温度峰值。在CPU利用率为80%,新风温度为20℃的条件下,与传统控制方法相比,该方法节能37.6%以上。
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Cooling control restraining effects due to ICT equipment utilization of disturbance based on model predictive control for modular data center
This paper proposes a cooling control method that reduces spikes in CPU temperature that occur due to fluctuation in the utilization of information communication technology (ICT) equipment based on model predictive control (MPC) for a modular datacenter. To cope with the fluctuations, the proposed method not only considers the server power consumption using a prediction model, but also switches between an MPC controller and a necessary-air-volume controller based on the rate at which server power consumption rises. The MPC controller controls the CPU temperature in order to do three things simultaneously: avoid throttling the operation of the CPU, reduce as much as possible the power consumed by data center cooling fans, and adjust for the effects of fluctuations. The necessary-air-volume controller calculates the command value of the revolution speed of the cooling fans to supply the air volume required during maximum CPU utilization. The results of our control simulation show that the proposed control method can drastically reduce spikes in CPU temperature. The proposed method provided energy savings of more than 37.6% compared to the conventional control method under conditions where the CPU utilization is 80% and the fresh air temperature is 20°C.
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