融合数据驱动场景生成的数据中心电-热-算耦合系统双层扩展规划方法OA

This work proposes a data-driven expansion planning solution,aiming at environmentally friendly upgrading and uncertainty modelling of data centers(DCs).Firstly,a multi-channel one-dimensional U-net based diffusion model is designed to generate scenarios of source-load multivariate time series,thus coping with the uncertainties.Then,an electricity-heat-computation coupling system expansion model is established,which considers CPU temperature constraints and individual status of servers with the objective of minimizing performance cost.To deal with the non-linearity of server model,a heuristic bi-level solving scheme is presented.At the upper level,the configured number of servers is determined by heuristic algorithm and transferred to the lower lever as a constant,thus making the planning model linear.At the lower level,the planning model is directly solved by commercial solver,and the performance cost is submitted back to the upper level,thereby iteratively obtaining the optimal capacities of servers,cooling systems and energy equipment.Based on a modified 18-node district heating system and an IEEE-14 bus power system,the numerical results confirm that the proposed solution can effectively characterize the source-load uncertainties,improve the energy efficiency and reduce economic cost of DCs.