李彬, 杜亚彬, 曹望璋, 祁兵, 孙毅, 陈宋宋. 考虑风光储互补与工作负载分配的数据中心优化调度[J]. 现代电力, 2022, 39(3): 356-362. DOI: 10.19725/j.cnki.1007-2322.2021.0129
引用本文: 李彬, 杜亚彬, 曹望璋, 祁兵, 孙毅, 陈宋宋. 考虑风光储互补与工作负载分配的数据中心优化调度[J]. 现代电力, 2022, 39(3): 356-362. DOI: 10.19725/j.cnki.1007-2322.2021.0129
LI Bin, DU Yabin, CAO Wangzhang, QI Bing, SUN Yi, CHEN Songsong. Optimal Scheduling of Data Center Considering Wind-Solar-Storage Complementary and Workload Distribution[J]. Modern Electric Power, 2022, 39(3): 356-362. DOI: 10.19725/j.cnki.1007-2322.2021.0129
Citation: LI Bin, DU Yabin, CAO Wangzhang, QI Bing, SUN Yi, CHEN Songsong. Optimal Scheduling of Data Center Considering Wind-Solar-Storage Complementary and Workload Distribution[J]. Modern Electric Power, 2022, 39(3): 356-362. DOI: 10.19725/j.cnki.1007-2322.2021.0129

考虑风光储互补与工作负载分配的数据中心优化调度

Optimal Scheduling of Data Center Considering Wind-Solar-Storage Complementary and Workload Distribution

  • 摘要: 随着 “双碳”目标的推进,数据中心新能源微电网不断发展,为减少数据中心综合运行成本与碳排放,提出了一种考虑风光储互补与工作负载分配的数据中心多目标优化调度模式。利用风光储互补在一定程度上解决新能源出力的间歇性;利用负载分配策略,使数据中心的用能需求尽可能与新能源出力曲线相匹配,提高新能源的利用率,减少碳排放。最后通过算例分析该模式下的优化调度结果,并比较不同运行模式下,数据中心的综合运行成本、碳排放量和新能源利用率。结果表明,该模式可明显降低运行成本与碳排放并提高新能源利用率。

     

    Abstract: Along with the progress of the two carbon emission goals in China, i.e., the carbon emission reaches its peak value in 2030 and the carbon neutral will be realized in 2060, the renewable energy microgrid in data center keeps continuous development. To reduce the carbon emission and comprehensive operating cost of data center, a multi-objective optimal scheduling mode of data center considering wind-solar-storage complementarity and load distribution was proposed. Firstly, wind-solar-storage complementarity was used to solve the intermittency of renewable energy output to a certain extent. Secondly, the workload distribution strategy was used to make energy demand of the data center matching with the renewable energy output curve as much as possible, so as to improve the utilization rate of renewable energy and reduce carbon emissions. Finally, the optimal scheduling results were analyzed by computing example under the proposed mode, and the comprehensive operation cost, carbon emission and renewable energy utilization rate of the data center under different operation modes were compared. Comparison results show that the proposed mode can significantly reduce carbon emissions and improve the utilization rate of renewable energy.

     

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