Collaborative Operation Mechanism of Computing Power and Electric Power Based on Day-ahead and Real-time Two-stage Power Balance

LIANG Xiuzhuang; GUO Caishan; TANG Wenhu; LI Mingze; WEN Rou; JING Zhaoxia

doi:10.7500/AEPS20250620003

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Collaborative Operation Mechanism of Computing Power and Electric Power Based on Day-ahead and Real-time Two-stage Power Balance

更新时间：2026-09-28

- Collaborative Operation Mechanism of Computing Power and Electric Power Based on Day-ahead and Real-time Two-stage Power Balance
- Automation of Electric Power Systems Pages: 1-24(2026)
- 作者机构：
  
  1.华南理工大学电力学院，广东省广州市 510641
  2.南方电网能源发展研究院有限责任公司配电网规划研究部，广东省广州市 510663
- 作者简介：
- 基金信息：
  
  Key Area Research and Development Program of Guangdong Province(2023B0909040003)
- DOI：10.7500/AEPS20250620003
  CLC：
- Received：20 June 2025，
  
  Revised：2026-02-09，
  
  Online First：29 June 2026，
- 稿件说明：
移动端阅览
梁秀壮,郭采珊,唐文虎等.基于日前-实时两阶段电力平衡的算力-电力协同运行机制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250620003.

LIANG Xiuzhuang,GUO Caishan,TANG Wenhu,et al.Collaborative Operation Mechanism of Computing Power and Electric Power Based on Day-ahead and Real-time Two-stage Power Balance[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250620003.
梁秀壮,郭采珊,唐文虎等.基于日前-实时两阶段电力平衡的算力-电力协同运行机制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250620003. DOI：

LIANG Xiuzhuang,GUO Caishan,TANG Wenhu,et al.Collaborative Operation Mechanism of Computing Power and Electric Power Based on Day-ahead and Real-time Two-stage Power Balance[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250620003. DOI：

摘要

以算力中心为核心构建的算力网络是调节潜力可观的需求侧可调节资源，也是提升电网灵活性、有效应对高比例可再生能源接入所带来电力平衡挑战的重要平衡资源。然而，算力中心无法准确获知电网平抑新能源波动性的调节需求，电网也难以有效激励算力中心的调节潜力。为解决上述难题，提出一种考虑配电系统运营商和云服务提供商2类主体互动关系的算力-电力协同运行机制：配电网系统运营商负责组织本地电力市场以及市场价格出清，云服务提供商则根据市场价格优化和调整算力中心平衡策略和用能行为。其次，引入双层两阶段鲁棒优化模型，用以刻画配电系统运营商与云服务提供商在日前电能量市场和实时平衡服务市场中的互动决策与联合出清过程，将算力中心的日前基线负荷以及实时负荷调节特性纳入到上层模型中，并基于不确定节点边际成本得到电网实时平衡价格，以反映电网不同节点、不同时刻对调节资源的需求，从而实现调节资源和可再生能源平衡需求的匹配。最后，结合仿真算例验证表明，所提机制可以引导算力中心按照电网平抑新能源波动性需求调整用电负荷，有效降低电网运行成本，并提高算力中心运营收益。

Abstract

The computing power network is constructed around computing centers. It is the adjustable resource on the demand side with considerable regulation potential

and is also an important balancing resource for enhancing power grid flexibility and effectively addressing power balance challenges brought by the high-level penetration of renewable energy. However

computing power centers cannot accurately obtaind the regulation requirement of powe grids for suppressing fluctuations in renewable energy sources

while power grids also have difficulties to effectively stimulate the regulation potential of computing power centers. To resolve the aforementioned difficult problems

this paper proposes a collaborative operation mechanism that considers the interactive relationship between two types of entities such as the distribution system operators (DSOs) and the cloud service providers (CSP). The DSOs are responsible for organizing the local electricity market and market prices clearing

while the CSPs optimize and adjust the balancing strategies and energy consumption behaviors of computing power centers according to market prices. Subsequently

a bilevel two-stage robust optimization model is introduced to characterize interactive decision-making and joint clearing process between the DSOs and CSPs in the day-ahead electric power energy market and real-time balance service market. The day-ahead load baseline and real-time load regulation characteristics of computing power centers are incorporated into the upper-level model. Based on the uncertaint locational marginal cost

the real-time balance price of power grids is derived to reflecte the demand for regulation resources at different nodes and time periods across power grids

thereby achieving an effective match between regulation resources and renewable energy balancing requirement. Finally

verification through simulation cases shows that the proposed market mechanism can guide computing power centers to adjust their power consumption load according to the power grid requirement for mitigating renewable energy fluctuations

and can effectively reduce power grid operation costs

while improving the operation revenues of computing power centers.

关键词

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references

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