1.State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University), Chongqing 400044, China;2.State Grid Xinjiang Electric Power Corporation, Urumqi 830011, China

In the era of big data, the scale of data centers is getting bigger and bigger, and the problem of high energy consumption is becoming more and more prominent. At present, the total energy consumption of data centers in China accounts for about 2.7% of the total electricity consumption of the society, and the research on energy efficiency optimization has become a hot topic in recent years. However, the current research ignores the inter-period start-stop-standby relationship and ramping constraints of information technology (IT) equipment and air-conditioning equipment, and the single-period optimal strategy given by it may cause frequent start-up of IT equipment between adjacent periods during actual operation. Due to excessive IT equipment loss or rapid growth in computing power demand, it is impossible to balance the computing power supply and demand immediately. Therefore, the energy efficiency optimization modeling of data centers must consider the time period coupling. Based on this, by comprehensively considering the energy consumption characteristics and heat exchange coupling relationship between IT equipment and air-conditioning equipment in data centers, as well as the inter-period start-stop-standby relationship and ramping constraints of IT equipment, an energy efficiency optimization model of data centers based on multi-period equipment coupling is established. To solve the computational efficiency problems caused by time coupling constraints and a large number of integer variables produced by the large number of IT equipment, a forward-looking decoupling algorithm and an IT equipment aggregation algorithm are separately proposed. Finally, a large-scale data center simulation example of 100 000 IT equipment is used to verify the practicability and high-efficiency of the proposed method.