Multi-timescale optimization scheduling of interconnected data centers based on model predictive control  

作　　者：Xiao GUO Yanbo CHE Zhihao ZHENG Jiulong SUN 

机构地区：[1]Energy Power,Electrical Automation and Information Engineering,Tianjin University,Tianjin 300072,China

出　　处：《Frontiers in Energy》2024年第1期28-41,共14页能源前沿（英文版）

摘　　要：With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids.In this paper,a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs)based on model predictive control(MPC),including day-ahead optimization,intraday rolling optimization,and intraday real-time correction.The day-ahead optimization stage aims at the lowest operating cost,the rolling optimization stage aims at the lowest intraday economic cost,and the real-time correction aims at the lowest power fluctuation,eliminating the impact of prediction errors through coordinated multi-timescale optimization.The simulation results show that the economic loss is reduced by 19.6%,and the power fluctuation is decreased by 15.23%.

关 键 词：model predictive control interconnected data center multi-timescale optimized scheduling distributed power supply/landscape uncertainty 

分 类 号：TK01[动力工程及工程热物理]