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Development of Predictive Control System Using Just-In-Time Modeling and Enthalpy-Aware Control in Air Conditioners for Large-Scale Data Center

机译:大型数据中心空调实时建模与焓觉控制的预测控制系统开发

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In this research, we propose an energy-efficient predictive control system with outside-air-introduced-type air conditioner in large-scale data center. The system consists of two parts; a predictive part and a control part. We propose to use a dynamic model construction technique called just-in-time (JIT) modeling in the predictive part. It can estimate the air temperature and humidity in the DC room and temperature at the inlet of servers at a high accuracy while the update of data center model is constructed naturally. We also propose to use a control algorithm that utilizes air enthalpy at outside and DC room in addition to the air temperature and humidity in the control part. Owing to the enthalpy, we achieve an effective energy-saving with both wet and dry air. We introduced this predictive control system to a large-scale data center and had verified the improvement in the energy-saving performance for few month. The air temperature and humidity after one hour could be successfully estimated with an accuracy of correlation coefficient of 0.97 or more using the proposed JIT modeling. Furthermore, we demonstrated that the power consumption of the DC room was significantly reduced by 28.9% using the proposed control algorithm compared to that of the conventional control algorithm.
机译:在这项研究中,我们提出了一种在大型数据中心中采用引入外部空气的空调的节能预测控制系统。该系统由两部分组成;预测部分和控制部分。我们建议在预测部分中使用称为实时(JIT)建模的动态模型构建技术。它可以自然准确地构建数据中心模型的更新,从而可以高精度地估算出直流机房中的空气温度和湿度以及服务器入口处的温度。我们还建议使用一种控制算法,该算法除了控制部分中的空气温度和湿度外,还利用室外和DC室中的空气焓。由于具有这种焓,我们在湿空气和干空气中均实现了有效的节能。我们将这种预测控制系统引入了大型数据中心,并在数月内验证了节能性能的提高。使用所提出的JIT模型可以成功地估计一小时后的空气温度和湿度,且相关系数的精度为0.97或更高。此外,我们证明,与传统控制算法相比,使用所提出的控制算法,直流机房的功耗显着降低了28.9%。

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