基于数据挖掘方法的数据中心能耗与空调系统关键参数量化关系研究

Quantitative relation between energy consumption and key air conditioning system parameters in data centers based on data mining method

使用Lasso回归筛选和人工参数筛选2种方式确定了数据中心能耗预测模型的输入参数,利用XGBoost算法对北京某数据中心的能耗和空调系统数据进行了数据挖掘,实现了对该数据中心电能利用效率(PUE)的准确预测,并得到了空调系统参数对PUE的定量化影响相关性排序。验证了使用数据挖掘方法筛选预测模型参数的可靠性。

Aiming at solving the problems of abnormal operation of frequency conversion air conditioning units caused by the weak heat dissipation of electronic components,uses Fluent software to simulate the flow and heat transfer characteristics of the plate-fin radiators for electronic components and the surrounding air flow field.Establishes a calculation model,compares with the experimental parameters,and the simulation calculation error is less than 10.8%.Carries out a simulation study on the original plate-fin radiators.The results indicate that the plate-fin radiators with one-way long fin have poor heat dissipation efficiency under the low wind speed,because of the low air flow and high temperature at the end of the radiators.Proposes a new type of plate-fin radiator,which adopts multi-segment fins and staggered fin structure,and the heat dissipation effect is greatly improved.The temperature of each component is reduced by 2.8 to 4.6℃after optimization,and the optimization efficiency is about 3.2%to 5.5%.