Datacenter Power Consumption Regulation towards Specific Targets in Smart Grid Environment

Abstract

With the large-scale grid connection of renewable energy sources, the frequency stability problem of the power system has become increasingly prominent. At the same time, the development of cloud computing has attracted people's attention to the high energy consumption characteristics of datacenters. Therefore, it was proposed to use the characteristics of the large load and high flexibility of the datacenters to respond to the demand response signal of the smart grid to maintain the stability of the power system. Specifically, this paper establishes a model that integrates multiple methods to precisely control the power consumption of the datacenter to minimize the total adjustment cost. First, according to the overall power consumption characteristics of the datacenter, the power consumption models of server and cooling system were established. Secondly, by controlling the temperature, different kinds of energy storage devices, load characteristics and server characteristics, the working process of various control methods and the corresponding operating cost model were obtained. Then, the operational cost and the adjustment penalty of each power regulation method were normalized to the total cost of datacenter. Finally, the proposed dynamic optimal scheduling method is used to achieve the goal of accurately adjusting the power consumption of the datacenter to minimize the total adjustment cost. Through comparative analysis with the control experimental group, the results show that the proposed method can better regulate the power consumption of the datacenter towards predefined targets with much less cost.