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Desynchronized Model Predictive Control for Large Populations of Fans in Server Racks of Datacenters

机译:数据中心服务器机架中大量风扇的非同步模型预测控制

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摘要

The aim of this paper is to mitigate the problem of high power demand peak and load oscillations in the operation of a large population of thermostatically controlled loads (TCLs) operated by model predictive control (MPC) at the TCL level. Two desynchronized MPC schemes are introduced: 1) adding random delays in reference signals and 2) extra penalizations on MPC objective functions. For characterizing and validating the proposed desynchronization MPC schemes, a partial differential equation (PDE) model is developed to represent the evolution of the operational states of the TCLs controlled by MPC in a population. The focus of this paper is put on the control of cooling fans in server racks of datacenters, whereas the proposed approach is applicable to other types of TCLs. Numerical simulation studies are carried out and the obtained results confirm the validity and the applicability of the developed approach.
机译:本文的目的是缓解由模型预测控制(MPC)在TCL级别上运行的大量恒温控制负载(TCL)的运行中出现高功率需求峰值和负载振荡的问题。引入了两种不同步的MPC方案:1)在参考信号中添加随机延迟,以及2)对MPC目标函数的额外惩罚。为了表征和验证提出的去同步MPC方案,开发了偏微分方程(PDE)模型来表示人口中受MPC控制的TCL的运行状态的演变。本文的重点放在数据中心服务器机架中冷却风扇的控制上,而所提出的方法适用于其他类型的TCL。进行了数值模拟研究,得到的结果证实了该方法的有效性和适用性。

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