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1.贵州电网有限责任公司电网规划研究中心,贵阳 550002
2.贵州电网有限责任公司电力调度控制中心,贵阳 550002
Received:10 March 2026,
Revised:2026-05-15,
Accepted:23 June 2026,
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Yang Dong-jun-ming, FAN Jun-qiu, LI Qing-sheng, et al. Coordinated Optimal Dispatch of Energy-Storage-Based Uninterruptible Power Supply in Data Centers and Integrated Energy Systems[J/OL]. Telecommunications Science, 2026.
Yang Dong-jun-ming, FAN Jun-qiu, LI Qing-sheng, et al. Coordinated Optimal Dispatch of Energy-Storage-Based Uninterruptible Power Supply in Data Centers and Integrated Energy Systems[J/OL]. Telecommunications Science, 2026. DOI: 10.11959/j.issn.1000-0801.DXKX260163.
为了解决为数据中心供能时存在的可再生能源消纳率低、运行成本高、不间断电源的调节潜力未能得到充分利用等问题,该研究构建了一种基于数据中心储能型不间断电源(EUPS)的综合能源系统双层优化调度模型。上层以降低可再生能源弃电和系统的运行成本为目标,优化设备运行策略,下层利用模型预测控制(MPC)减少EUPS的荷电状态波动。案例结果表明,该方案可使系统运行成本较无储能基线降低9.3%,MPC的引入使得较无MPC控制时运行成本上升3.5%,但电池等效循环寿命提升41.4%。该方案较无储能时可使风机光伏弃电减少19.7%,且在调度过程中,EUPS的荷电状态与其初始值的平均绝对误差相对于无MPC控制时减少31.25%。研究结果表明,所提方案能够有效提升数据中心微电网的可再生能源消纳能力和系统的运行灵活性,为绿电直供背景下数据中心源网荷储协同运行提供参考。
To address the issues of low renewable energy consumption
high operational costs
and the underutilization of the regulation potential of uninterruptible power supply (UPS) when supplying energy to data centers
this paper proposes a bi-level optimal dispatch model for an integrated energy system based on energy-storage-based uninterruptible power supply (EUPS) in data centers. The upper-level model aims to minimize renewable energy curtailment and overall system operating costs by optimizing the operational strategies of system components
while the lower-level model employs model predictive control (MPC) to reduce fluctuations in the state of charge (SOC) of the EUPS. Case study results demonstrate that the proposed approach can reduce system operating costs by 9.3%
decrease wind and photovoltaic curtailment by 19.7%
and reduce the mean absolute error of the SOC by 31.25%. The results indicate that the proposed method effectively enhances renewable energy utilization and operational flexibility in data center microgrids
providing a useful reference for the coordinated operation of source–grid–load–storage systems for data centers under the paradigm of direct green power supply.
Koot M , Wijnhoven F . Usage impact on data center electricity needs: a system dynamic forecasting model [J ] . Applied Energy , 2021 , 291 : 116798 . DOI: 10.1016/j.apenergy.2021.116798 http://dx.doi.org/10.1016/j.apenergy.2021.116798 .
中国信息通信研究院 , 内蒙古和林格尔新区管委会 。 绿色算力发展研究报告(2025 年) [R ] . 北京 : 中国信息通信研究院 , 2025 .
CAICT, Inner Mongolia Horinger New Area Management Committee . Green Computing Power Development Research Report (2025) [R ] . Beijing : CAICT , 2025 .
Khosravi A , Sandoval O R , Taslimi M S , et al . Review of energy efficiency and technological advancements in data center power systems [J ] . Energy and Buildings , 2024 : 114834 . DOI: 10.1016/j.enbuild.2024.114834 http://dx.doi.org/10.1016/j.enbuild.2024.114834 .
Guo S , Kurban A , He Y , et al . Multi-objective sizing of solar-wind-hydro hybrid power system with doubled energy storages under optimal coordinated operational strategy [J ] . CSEE Journal of Power and Energy Systems , 2023 , 9 ( 6 ): 2144 - 2155 . DOI: 10.17775/CSEEJPES.2021.00190 http://dx.doi.org/10.17775/CSEEJPES.2021.00190 .
Fu C , Zhang W . Stochastic optimization of photovoltaic-integrated data centers with hybrid cooling and waste heat recovery for district energy supply [J ] . Renewable Energy , 2026 , 256 ( 1 ): 124248 . DOI: 10.1016/j.renene.2025.124248 http://dx.doi.org/10.1016/j.renene.2025.124248 .
Guo C , Luo F , Cai Z , et al . Integrated planning of internet data centers and battery energy storage systems in smart grids [J ] . Applied Energy , 2021 , 281 : 116093 . DOI: 10.1016/j.apenergy.2020.116093 http://dx.doi.org/10.1016/j.apenergy.2020.116093 .
Thompson C C , Oikonomou K , Etemadi A H , et al . Optimization of data center battery storage investments for microgrid cost savings, emissions reduction, and reliability enhancement [C ] // IEEE Industry Applications Society Annual Meeting . Piscataway : IEEE , 2015 . DOI: 10.1109/IAS.2015.7356940 http://dx.doi.org/10.1109/IAS.2015.7356940 .
Cao F , Wang Y , Zhu F , et al . UPS node-based workload management for data centers considering flexible service requirements [J ] . IEEE Transactions on Industry Applications , 2019 , 55 ( 6 ): 5533 - 5542 . DOI: 10.1109/TIA.2019.2933791 http://dx.doi.org/10.1109/TIA.2019.2933791 .
Li J , Wang S , Ye L , et al . An integrated optimization framework unlocks energy storage economic value in renewable energy bases through planning operation coordination [J ] . Discover Applied Sciences , 2026 , 8 ( 1 ): 59 .
Wang K , Ye L , Yang S , et al . A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control [J ] . Applied Energy , 2023 , 331 : 120414 . DOI: 10.1016/j.apenergy.2022.120414 http://dx.doi.org/10.1016/j.apenergy.2022.120414 .
Peng X , Bhattacharya T , Cao T , et al . Exploiting renewable energy and UPS systems to reduce power consumption in data centers [J ] . Big Data Research , 2022 , 27 : 100306 . DOI: 10.1016/j.bdr.2021.100306 http://dx.doi.org/10.1016/j.bdr.2021.100306 .
Ye G , Gao F , Fang J , et al . Joint workload scheduling in geo-distributed data centers considering UPS power losses [J ] . IEEE Transactions on Industry Applications , 2023 , 59 ( 1 ): 612 - 626 . DOI: 10.1109/TIA.2022.3214186 http://dx.doi.org/10.1109/TIA.2022.3214186 .
ALAPERÄ I , HONKAPURO S , TIKKA V , et al . Dual-purposing UPS batteries for energy storage functions: a business case analysis [J ] . Energy Procedia , 2019 , 158 : 5061 - 5066 . DOI: 10.1016/j.egypro.2019.01.645 http://dx.doi.org/10.1016/j.egypro.2019.01.645 .
Iovine A , Rigaut T , Damm G , et al . Power management for a DC microgrid integrating renewables and storages [J ] . Control Engineering Practice , 2019 , 85 : 59 - 79 . DOI: 10.1016/j.conengprac.2019.01.009 http://dx.doi.org/10.1016/j.conengprac.2019.01.009 .
Zafar R , Ravishankar J , Fletcher J E , et al . Multi-timescale model predictive control of battery energy storage system using conic relaxation in smart distribution grids [J ] . IEEE Transactions on Power Systems , 2018 , 33 ( 6 ): 7152 - 7161 . DOI: 10.1109/TPWRS.2018.2847400 http://dx.doi.org/10.1109/TPWRS.2018.2847400 .
Li D , Ren L . Two-time scale microgrid scheduling based on power fluctuation mitigation priority and model predictive control [J ] . Energy , 2025 , 324 : 135760 . DOI: 10.1016/j.energy.2025.135760 http://dx.doi.org/10.1016/j.energy.2025.135760
Zhang X , Wang B , Gamage D , et al . Model predictive and iterative learning control based hybrid control method for hybrid energy storage system [J ] . IEEE Transactions on Sustainable Energy , 2021 , 12 ( 4 ): 2146 - 2158 . DOI: 10.1109/TSTE.2021.3083902 http://dx.doi.org/10.1109/TSTE.2021.3083902 .
Ren F , Wang J , Zhu S , et al . Multi-objective optimization of combined cooling, heating and power system integrated with solar and geothermal energies [J ] . Energy Conversion and Management , 2019 , 197 : 111866 . DOI: 10.1016/j.enconman.2019.111866 http://dx.doi.org/10.1016/j.enconman.2019.111866 .
Ma Z , Dong F , Wang J , et al . Optimal design of a novel hybrid renewable energy CCHP system considering long and short-term benefits [J ] . Renewable Energy , 2023 , 206 : 72 - 85 . DOI: 10.1016/j.renene.2023.02.014 http://dx.doi.org/10.1016/j.renene.2023.02.014 .
He J , Guo Z , Li Y . Multi-objective optimization of district cooling systems considering cooling load characteristics [J ] . Energy Conversion and Management , 2023 , 281 : 116823 . DOI: 10.1016/j.enconman.2023.116823 http://dx.doi.org/10.1016/j.enconman.2023.116823 .
叶杨莉 . 考虑风电不确定性的综合能源系统协同优化调度 [D ] . 杭州 : 浙江大学 , 2021 .
Ye Yangli . Cooperative Optimal Dispatching of Integrated Energy System Considering Wind Power Uncertainty [D ] . Hangzhou : Zhejiang University , 2021 .
席裕庚 . 预测控制 [M ] . 2版 . 北京 : 国防工业出版社 , 2013 .
Xi Yugeng . Predictive Control [M ] . 2nd ed . Beijing : National Defense Industry Press , 2013 .
郭宏民 . 一类受限混杂系统的预测控制研究 [D ] . 无锡 : 江南大学 , 2008 .
Guo Hongmin . Predictive Control for a Class of Constrained Hybrid Systems [D ] . Wuxi : Jiangnan University , 2008 .
席裕庚 , 李德伟 , 林姝 . 模型预测控制——现状与挑战 [J ] . 自动化学报 , 2013 , 39 ( 3 ): 222 - 236 .
Xi Yugeng , Li Dewei , Lin Shu . Model Predictive Control — Status and Challenges [J ] . Acta Automatica Sinica , 2013 , 39 ( 3 ): 222 - 236 .
翟晶晶 。 计及供能不确定性的区域综合能源系统日前-日内协调调度 [D ] . 南京 : 南京理工大学 , 2022 .
Zhai Jingjing . Day-ahead and Intra-day Coordinated Scheduling of Regional Integrated Energy Systems Considering Energy Supply Uncertainties [D ] . Nanjing : Nanjing University of Science and Technology , 2022 .
Yan G , Liu D , Li J , et al . A cost accounting method of the Li-ion battery energy storage system for frequency regulation considering the effect of life degradation [J ] . Protection and Control of Modern Power Systems , 2018 , 3 : 4 . DOI: 10.1186/s41601-018-0076-2 http://dx.doi.org/10.1186/s41601-018-0076-2 .
Wang J , Zhai Z , Jing Y , et al . Particle swarm optimization for redundant building cooling heating and power system [J ] . Applied Energy , 2010 , 87 ( 12 ): 3668 - 3679 . DOI: 10.1016/j.apenergy.2010.06.021 http://dx.doi.org/10.1016/j.apenergy.2010.06.021 .
He Y , Guo S , Zhou J , et al . Multi-objective planning-operation co-optimization of renewable energy system with hybrid energy storages [J ] . Renewable Energy , 2022 , 184 : 776 - 790 . DOI: 10.1016/j.renene.2021.11.116 http://dx.doi.org/10.1016/j.renene.2021.11.116 .
Ju L , Tan Z , Li H , et al . Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China [J ] . Energy , 2016 , 111 : 322 - 340 . DOI: 10.1016/j.energy.2016.05.085 http://dx.doi.org/10.1016/j.energy.2016.05.085 .
Wei D , Chen A , Sun B , et al . Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system [J ] . Energy , 2016 , 98 : 296 - 307 . DOI: 10.1016/j.energy.2016.01.027 http://dx.doi.org/10.1016/j.energy.2016.01.027 .
Ghamari S , Ghahramani M , Habibi D , et al . Improved performance of battery energy storage in a wind energy conversion system using an optimal PID controller [C ] // 2024 IEEE 34th Australasian Universities Power Engineering Conference (AUPEC) . Piscataway : IEEE , 2024 : 1 - 6 .
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