
上海交通大学电气工程学院,上海市 200240
Received:19 March 2026,
Revised:2026-07-06,
Online First:05 August 2026,
Published:10 October 2026
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冯洪赟,谭振飞,严正.基于空间弹性表征的广域数据中心集群算电协同调度方法[J].电力系统自动化,2026,50(19):110-123.
FENG Hongyun,TAN Zhenfei,YAN Zheng.Computing Power-Electric Power Coordinated Dispatch Method for Wide-area Data Center Clusters Based on Spatial Flexibility Characterization[J].Automation of Electric Power Systems,2026,50(19):110-123.
冯洪赟,谭振飞,严正.基于空间弹性表征的广域数据中心集群算电协同调度方法[J].电力系统自动化,2026,50(19):110-123. DOI: 10.7500/AEPS20260319001.
FENG Hongyun,TAN Zhenfei,YAN Zheng.Computing Power-Electric Power Coordinated Dispatch Method for Wide-area Data Center Clusters Based on Spatial Flexibility Characterization[J].Automation of Electric Power Systems,2026,50(19):110-123. DOI: 10.7500/AEPS20260319001.
人工智能浪潮下数据中心(特别是智算中心)的快速发展在带来电力负荷增长的同时,也成为重要的电力灵活性来源。数据中心集群可通过计算任务转移实现用电需求的空间迁移,其电力负荷具有空间弹性,对新能源电力系统安全经济运行具有重要价值。然而,数据中心与电力系统分属不同运营主体,无法接受电网统一调度。如何实现广域算力调度与电力系统运行的协同决策,面临技术挑战。首先,考虑计算任务空间转移成本与约束,构建数据中心集群与电力系统协同优化调度模型。然后,提出基于可行域投影的数据中心集群空间弹性表征方法,将计算任务调度模型降维至用电功率空间,显式刻画空间弹性的可行边界和价格敏感度。最后,提出计及空间弹性的非迭代式算电协同调度方法,证明该方法的最优性与隐私保护能力。算例分析验证了所提方法在降低运行成本、缓解输电阻塞、促进新能源消纳、提高协调优化计算效率方面的有效性。
Under the wave of artificial intelligence
the rapid development of data centers (especially artificial intelligence data centers) has brought growth in power load and they become an important source of power system flexibility. Data center clusters can achieve spatial migration of electricity demand through computational task transfer. Its power load exhibits spatial flexibility
which holds significant value for power system security and economic operation. However
data centers and power systems belong to different operating entities
making them unable to accept unified dispatch from the power grid. How to achieve coordinated decision-making between wide-area computing power dispatch and power system dispatch faces technical challenges. First
considering spatial computational task transfer costs and constraints
a coordinated optimal dispatch model between data center clusters and power systems is constructed. Then
a feasible region projection-based spatial flexibility characterization method for data center clusters is proposed. It reduces the dimensionality of the computational task dispatch model to the electricity consumption power space to explicitly characterize feasible boundaries and price sensitivity of spatial flexibility. Finally
a spatial flexibility-incorporated non-iterative computing power-electric power coordinated dispatch method is proposed. The optimality and privacy-preserving capabilities of the proposed method are proven. Case studies verify the effectiveness of the proposed method in reducing operating costs
mitigating grid congestion
promoting renewable energy accommodation
and improving coordinated optimal computational efficiency
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