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Cooling control based on model predictive control using temperature information of IT equipment for modular data center utilizing fresh-air

机译:基于模型预测控制的冷却控制,该模型使用IT设备的温度信息,用于模块化数据中心的新鲜空气

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A cooling control method based on a model predictive control (MPC) for a modular datacenter utilizing the fresh-air is proposed. The proposed method reduces the total energy consumption of information technology (IT) equipment and cooling facilities in the data center, while considering a relationship between energy-savings and the temperature information of IT equipment. This method based on MPC controls the central processing unit (CPU) temperature in servers by facility fans for cooling. To design the proposed method, it is developed a prediction model that represents the CPU temperature by the revolution speed of facility fans, the fresh-air temperature, utilization of servers, and other factors. Furthermore, the proposed control method is applied to the actual modular data center. The energy consumption of the proposed method is compared with that of a traditional method, which has controlled the temperature difference between the inlet and outlet of the server racks based on proportional integral (PI) control. Actual comparison experiments with traditional method are provided to validate effectiveness of the proposed method. The results show that the proposed method realizes energy-savings of more than 20% compared to the traditional control method in the actual modular datacenter.
机译:提出了一种基于模型预测控制(MPC)的模块化数据中心利用新鲜空气的冷却控制方法。该方法减少了信息技术设备和数据中心冷却设备的总能耗,同时考虑了节能与IT设备温度信息之间的关系。这种基于MPC的方法通过设备风扇控制服务器中中央处理器(CPU)的温度以进行冷却。为了设计所提出的方法,建立了一个预测模型,该模型通过设施风扇的转速,新鲜空气温度,服务器利用率和其他因素来表示CPU温度。此外,所提出的控制方法被应用于实际的模块化数据中心。将该方法的能耗与传统方法的能耗进行比较,传统方法基于比例积分(PI)控制来控制服务器机架的入口和出口之间的温差。提供了与传统方法的实际比较实验,以验证该方法的有效性。结果表明,在实际的模块化数据中心中,与传统的控制方法相比,该方法实现了20%以上的节能效果。

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