计算资源共享模式下的托管式数据中心群两阶段鲁棒优化模型

Two Stage Robust Optimization Model of Colocation Data Centers Cluster Under Computing Resource Sharing Mode

城区高能耗且数量众多的中小型数据中心具有巨大的调节潜力,可作为需求响应业务的主要载体,然而此类数据中心的成果多是将个体作为研究对象,并未考虑多个数据中心计算资源联动的可能。对此,该文提出一种计算资源共享模式下的托管式数据中心群两阶段鲁棒优化模型。首先,将托管式数据中心群下的租户分为日前组和备用组。然后,日前组的租户参与需求响应,备用组的租户在Nash博弈的基础上共享计算资源给日前组,处理日前组的不确定性工作负载。最后,通过两阶段鲁棒优化模型拟定日前调节方案和备用调节方案。经仿真结果验证,该文所提的模型能提高数据中心运营商的整体收益,当负荷削减存在不确定性时,模型能减少数据中心运营商对柴油发电机的依赖。

A large number of small and medium-sized data centers with high energy consumption in urban areas have great potential for load regulation,which can be the main carriers for demand response programs.However,most researchers take such a single data center as the object of study without considering the possibility of integrating the computing resources of multiple data centers.Therefore,this paper proposes a two-stage robust optimization model for colocation data centers based on the computing resource sharing mode.First,tenants of the colocation data centers are divided into the day-ahead group and the backup group.Then,tenants of the day-ahead group participate in demand response,and that of the backup group use the Nash bargaining game to share their computing resources with the day-ahead group for calculating uncertain workload.Finally,the two-stage robust optimization model is applied to formulate day-ahead regulation and backup regulation plans.The simulation results show that the proposed model is able to improve the total payoff of the data center operator.The results also prove that the model will reduce the operator’s dependence on the diesel generators when there is uncertainty in the load reduction.