Abstract: The huge energy consumption of data centers brings pressure to economy and environment. Analysis and prediction of energy consumption is a promising way to reduce data center energy consumption. Energy consumption is affected by many complicated factors, including outdoor temperature, CPU load and etc. In this paper, a data center energy prediction model based on ANN(Artificial Neural Network) and GRU(Gated Recurrent Unit) is proposed. First, we analyze characteristics of energy consumption and select features that are related to energy consumption as much as possible. These time series characteristic data are used as input for model training. Then, the combination of ANN and GRU networks are used to predict energy consumption. Finally, based on the real trajectory data, it is verified and analyzed in the simulation environment.The experimental simulation results show that compared with Linear SVR, SVR, and ANN, the proposed method has higher prediction accuracy.