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To address the problems of high energy consumption in data centers and insufficient utilization of independent energy storage systems,a two-layer collaborative optimization scheduling method for a multi-data-center microgrid integrated with cloud energy storage is proposed. First,an operational model for multi-user participation in cloud energy storage is developed based on its characteristic features. Second,data center loads are categorized according to their response characteristics,and a spatiotemporal migration model is established.Subsequently,leveraging the integrated system architecture of cloud energy storage and the multi-data-center microgrid,we formulate a multi-time scale two-layer optimization model.The upper layer focuses on long-term capacity planning for cloud energy storage,while the lower layer optimizes operational strategies for the multi-microgrid system,which includes data centers,through short-term scheduling.By applying the KKT condition and the Big-M method,the original nonlinear two-layer model is reformulated into a single-layer linear optimization model.Simulation results show that the proposed method can increase the additional revenue of cloud energy storage system to5.543 million yuan,reduce the total cost of the data center microgrid system by 30.3%,improve the efficiency of resource utilization,and effectively realize the collaborative optimization of data center's adjustable load space-time migration and the cloud energy storage system.
[1] IEA(2025),Global Energy Review 2025,IEA,Paris.[EB/OL].(2025-03-01)[2025-06-27]https：//www.iea.org/reports/globalenergy-review-2025.
[2]林嘉瑜，韩俊涛，王永真，等.计及效率的低碳数据中心算力综合能源系统规划及运行优化[J/OL].上海交通大学学报：1-27[2025-06-27].https：//doi.org/10.16183/j.cnki.jsjtu.2023.528.LIN Jiayu,HAN Juntao,WANG Yongzhen,et al.Capacity planning and operational optimization for low-carbon data center integrated energy system considering exergy efficiency[J/OL]. Journal of Shanghai Jiaotong University:1-27[2025-06-27].https：//doi.org/10.16183/j.cnki.jsjtu.2023.528.
[3]文淅宇，朱继忠，李盛林，等.基于时空协同的多数据中心虚拟电厂低碳经济调度策略[J].电力系统自动化，2024,48(18):56-65.WEN Xiyu,ZHU Jizhong,LI Shenglin,et al.Low-carbon economic dispatch for multiple data center virtual power plant based on spatio-temporal collaboration[J]. Automation of Electric Power Systems,2024,48(18):56-65.
[4] ZARE GHALEH SEYYEDI A,AKBARI E,MAHMOUDI RASHID S,et al. Application of robust optimized spatiotemporal load management of data centers for renewable curtailment mitigation[J]. Renewable and Sustainable Energy Reviews,2024,204:114793.
[5]杨挺，姜含，侯昱丞，等.基于计算负荷时-空双维迁移的互联多数据中心碳中和调控方法研究[J].中国电机工程学报，2022,42(1):164-177.YANG Ting,JIANG Han,HOU Yucheng,et al. Study on carbon neutrality regulation method of interconnected multi-datacenter based on spatio-temporal dual-dimensional computing load migration[J].Proceedings of the CSEE,2022,42(1):164-177.
[6]秦雪雪，李泽宁，薛屹洵，等.计及建筑热动态特性的数据中心时空协调两阶段鲁棒优化方法[J].电力系统自动化，2025,49(11):59-69.QIN Xuexue,LI Zening,XUE Yixun,et al. Two-stage robust optimization method for spatio-temporal coordination of data center considering thermal dynamic characteristics of buildings[J].Automation of Electric Power Systems,2025,49(11):59-69.
[7]文亚凤，程祖铭，刘欣雅，等.考虑算力-电热耦合的边缘数据中心能量优化管理[J/OL].中国电机工程学报，1-12[2025-06-27]. https：//kns. cnki. net/kcms/detail/11.2107.tm.20250123.1539.012.html.WEN Yafeng,CHENG Zuming,LIU Xinya,et al.Considering the energy optimization management of edge data centers with computing power-electricity-heat coupling[J/OL].Proceedings of the CSEE,1-12[2025-06-27].https：//kns.cnki.net/kcms/detail/11.2107.tm.20250123.1539.012.html.
[8]曾博，刘一贤，张卫翔，等.综合考虑内外生不确定性的绿色数据中心多域资源协同规划方法[J].中国电机工程学报，2024,44(12):4732-4748.ZENG Bo,LIU Yixian,ZHANG Weixiang,et al. A collaborative optimization approach for green data center multi-domain resource planning considering both endogenous and exogenous uncertainties[J].Proceedings of the CSEE,2024,44(12):4732-4748.
[9] LI W W,QIAN T,ZHANG Y,et al.Distributionally robust chanceconstrained planning for regional integrated electricity-heat systems with data centers considering wind power uncertainty[J].Applied Energy,2023,336:120787.
[10]李林虹，贺帅佳，高红均，等.考虑能源站-变电站-数据中心站多站融合的配电网低碳规划方法[J/OL].电网技术，1-14[2025-06-27].https：//link.cnki.net/doi/10.13335/j.1000-3673.pst.2024.1934.LI Linhong,HE Shuaijia,GAO Hongjun,et al. A low-carbon planning method for distribution network considering multi-station integration of energy station,substation and data center[J/OL].Power System Technology,1-14[2025-06-27].https：//link.cnki.net/doi/10.13335/j.1000-3673.pst.2024.1934.
[11] ZHANG Y B,TANG H,LI H X,et al.Unlocking the flexibilities of data centers for smart grid services:optimal dispatch and design of energy storage systems under progressive loading[J]. Energy,2025,316:134511.
[12]周世博，周明，孙黎滢，等.激发多元灵活性的数据中心协同优化运行方法[J].电网技术，2024,48(11):4417-4426.ZHOU Shibo,ZHOU Ming,SUN Liying,et al.Optimal synergistic operation method for data center by activating multiple flexibilities[J].Power System Technology,2024,48(11):4417-4426.
[13] CHEN M,ZHAO Y X,LI Y X,et al.Optimal operation of Internet Data Center with PV and energy storage type of UPS clusters[J].Global Energy Interconnection,2024,7(1):61-70.
[14]王云鹏，胡健，张晓杰，等.云储能模式下分布式用户虚拟储能需求评估[J].可再生能源，2024,42(5):694-703.WANG Yunpeng,HU Jian,ZHANG Xiaojie,et al. Demand assessment for virtual energy storage of distributed user under the cloud mode[J]. Renewable Energy Resources,2024,42(5):694-703.
[15] LIU J K,ZHANG N,KANG C Q,et al. Cloud energy storage for residential and small commercial consumers:a business case study[J].Applied Energy,2017,188:226-236.
[16] SONG X H,QU Z W,WANG Y J,et al. Optimization of multienergy cloud energy storage for multi-microgrid system with hydrogen refueling station[J]. Renewable Energy,2025,241:122382.
[17]陈昌铭，张群，黄亦昕，等.考虑最优建设时序和云储能的园区综合能源系统优化配置方法[J].电力系统自动化，2022,46(2):24-32.CHEN Changming,ZHANG Qun,HUANG Yixin,et al. Optimal configuration method of park-level integrated energy system considering optimal construction time sequence and cloud energy storage[J].Automation of Electric Power Systems,2022,46(2):24-32.
[18]程杉，卢渊涛，王灿.考虑P2G-CCS-HFC协调运行的园区综合能源系统分布鲁棒优化调度[J].电力系统保护与控制，2025,53(10):87-101.CHENG Shan,LU Yuantao,WANG Can. Distributed robust optimal scheduling for a regional integrated energy system considering coordinated operation of P2G-CCS-HFC[J]. Power System Protection and Control,2025,53(10):87-101.
[19]陆宝奇，蒋伟，杨俊杰，等.基于云储能容量动态分配的微电网系统双层优化模型[J].现代电力，2025,42(1):19-27.LU Baoqi,JIANG Wei,YANG Junjie,et al. Double-layer optimization model for microgrid system based on dynamic capacity allocation of CES[J]. Modern Electric Power,2025,42(1):19-27.
[20]吴云芸，方家琨，艾小猛，等.计及需求响应的数据中心联盟共享储能规划[J].电力系统自动化，2023,47(7):42-50.WU Yunyun,FANG Jiakun,AI Xiaomeng,et al. Shared energy storage planning for data center alliance considering demand response[J].Automation of Electric Power Systems,2023,47(7):42-50.
[21]王继东，许秋铭，黄婷，等.含共享储能的数据中心微网群分布式优化调度[J].电网技术，2024,48(8):3238-3247.WANG Jidong,XU Qiuming,HUANG Ting,et al. Distributed optimal scheduling of data center microgrids cluster with shared energy storage[J].Power System Technology,2024,48(8):3238-3247.
[22] LUO S J,CHEN C M,QIU W Q,et al.Bi-layer optimal planning of rural distribution network based on KKT condition and Big-M method[J].Energy Reports,2021,7:637-644.
[23] NASROLAHPOUR E,KAZEMPOUR J,ZAREIPOUR H,et al. A bilevel model for participation of a storage system in energy and reserve markets[J]. IEEE Transactions on Sustainable Energy,2018,9(2):582-598.
[24] NIU T,HU B,XIE K G,et al.Spacial coordination between data centers and power system considering uncertainties of both source and load sides[J]. International Journal of Electrical Power&Energy Systems,2021,124:106358.
[25]耿圣杰，贾燕冰，江坷滕，等.电网数据中心服务器容量及其综合供能系统联合规划策略研究[J].电网技术，2022,46(9):3281-3292.GENG Shengjie,JIA Yanbing,JIANG Keteng,et al.Joint planning strategy of grid data center server capacity and its integrated energy supply system[J].Power System Technology,2022,46(9):3281-3292.
[26] Logs of Real Parallel Workloads from Production Syst-ems[EB/OL].(2019-09-24)[2025-06-27].https：//www.cs.huji.ac.il/labs/parallel/workload/logs.html.
[27]祁兵，曹望璋，李彬，等.计及负载特征及响应特性的多数据中心双层优化模型[J].电力系统自动化，2022,46(21):30-41.QI Bing,CAO Wangzhang,LI Bin,et al. Bi-level optimization model of multiple data centers considering workload features and response characteristics[J].Automation of Electric Power Systems,2022,46(21):30-41.
[28]吴盛军，李群，刘建坤，等.基于储能电站服务的冷热电多微网系统双层优化配置[J].电网技术，2021,45(10):3822-3832.WU Shengjun,LI Qun,LIU Jiankun,et al. Bi-level optimal configuration for combined cooling heating and power multimicrogrids based on energy storage station service[J]. Power System Technology,2021,45(10):3822-3832.
[29]栗然，吕慧敏，彭湘泽，等.阶梯成本下考虑混合租建模式的云储能优化配置[J].太阳能学报，2024,45(2):263-273.LI Ran,LYU Huimin,PENG Xiangze,et al.Optimal configuration of cloud energy storage consideing hybrid self-built and lease mode under tiered cost[J].Acta Energiae Solaris Sinica,2024,45(2):263-273.
[30] GAN W,AI X M,FANG J K,et al. Security constrained coplanning of transmission expansion and energy storage[J].Applied Energy,2019,239:383-394.
Basic Information:
DOI：10.20097/j.cnki.issn1007-9904.250395
China Classification Code:TM73
Citation Information:
[1]YUE Jiaming,ZHONG Jianwei,LIANG Huijun ,et al.Bi-level Optimal Scheduling of Cloud Energy Storage and Multi-microgrid System With Data Center[J].Shandong Electric Power,2025,52(10):91-101+112.DOI:10.20097/j.cnki.issn1007-9904.250395.
Fund Information:
国家自然科学基金项目（62163013）~~
2025-05-15
2025
2025-10-21
2025-07-10
2025
1
2025-10-25
2025-10-25