Energy Consumption Optimization Of A Large Data Center

Data center is a building place where a large number of computer servers are stored.Its rapid construction ensures the rapid development of information technology and brings a lot of economic benefits.With the deepening of its construction,the energy consumption problem of data center is becoming more and more serious.The power consumption of servers and air conditioning refrigeration system in data center is huge.And a lot of energy is wasted because of the lack of scientific and effective control measures.This paper analyzes the energy consumption composition of a large data center,and optimizes the energy consumption of its air conditioning and refrigeration system.Aiming at the problem of energy consumption in data center,this paper considers the machine heat production and air conditioning refrigeration in the data center room,so as to make the heat in the room within a reasonable limit as the basic condition,and establishes the optimization model of refrigeration energy consumption in the room.For this model,the LSTM neural network model is used to solve it by using the characteristics of the internal heat balance relationship of the data center,the time delay of the air conditioning effect,and the multi time influence of the temperature change.Through the actual case,the results show that the maximum error of the algorithm is 0.5centigrade,the average error is 0.35 centigrade,and all the nine temperatures in the case are distributed between 23.5 and 24.5 centigrade,which ensures that the temperature of the case reaches the standard.At the same time,the energy saving rate of air conditioning is about26%,which reduces the energy consumption of data center.The case shows that the algorithm adopted in this paper can control the temperature to reach the standard and save energy consumption without any change to the existing spatial layout of data center,and proves the rationality of the model and the effectiveness of the algorithm.