Energy Optimal Dispatch of the Data Center Microgrid Based on Stochastic Model Predictive Control

Abstract

Renewable energy outputs such as wind turbines and photovoltaics, as well as data center workloads are both random and uncertain. In order to enhance the stability and economy of the data center in actual operation effectively, a multi-time scale optimal dispatch method for the data center microgrid based on stochastic model predictive control is proposed in this paper. In the day-ahead scheduling stage, the characteristic of the data center that batch workloads are allowed to be served delayed is considered. And the scenario analysis method is applied to describe the uncertainty of loads and renewable energy outputs, based on which an economic optimization scheduling model is established to minimize the system operating cost. The intra-day scheduling utilizes the rolling optimization and feedback correction of model predictive control to correct the deviation of loads and renewable energy outputs and adjust the day-ahead dispatch plan in real time, which ensures the effectiveness of day-ahead plan and the stability of system operating. Through the simulation results of a typical data center microgrid, the effectiveness of the proposed method is verified.