首页|Multi-timescale optimization scheduling of interconnected data centers based on model predictive control
Multi-timescale optimization scheduling of interconnected data centers based on model predictive control
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
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％.
model predictive controlinterconnected data centermulti-timescaleoptimized schedulingdistributed power supplylandscape uncertainty
Xiao GUO、Yanbo CHE、Zhihao ZHENG、Jiulong SUN
展开 >
Energy Power,Electrical Automation and Information Engineering,Tianjin University,Tianjin 300072,China
NETL
NSTL
万方数据
