Reducing Power Consumption in Data Center by Predicting Temperature Distribution and Air Conditioner Efficiency with Machine Learning

To reduce the power consumption in data centers, the coordinated control of the air conditioner and the serversis required. It takes tens of minutes for changes of operationalparameters of air conditioners including outlet air temperatureand volume to be reflected in the temperature distribution inthe whole data center. So, the proactive control of the airconditioners is required according to the prediction temperaturedistribution corresponding to the load on the servers. In thispaper, the temperature distribution and the power efficiencyof air conditioner were predicted by using a machine-learningtechnique, and also we propose a method to follow-up proactivecontrol of the air conditioner under the predicted optimumcondition. Consequently, by the follow-up proactive control ofthe air conditioner and the load of servers, power consumptionreduction of 30% at maximum was demonstrated.