Computing-task-scheduling-driven Bidirectional Coordinated Optimization for Computing Power and Electric Power from Perspective of Cooperative Game

WANG Peng; LIU Wenyu; CAO Yujie; SUN Yimeng; WEI Xuan; DING Zhaohao

doi:10.7500/AEPS20251126001

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Computing-task-scheduling-driven Bidirectional Coordinated Optimization for Computing Power and Electric Power from Perspective of Cooperative Game

Computing Power-Electric Power Coordination | 更新时间：2026-09-01

- Computing-task-scheduling-driven Bidirectional Coordinated Optimization for Computing Power and Electric Power from Perspective of Cooperative Game
- Automation of Electric Power Systems Vol. 50, Issue 17, Pages: 62-73(2026)
- 作者机构：
  
  1.新能源电力系统全国重点实验室（华北电力大学），北京市 102206
  2.华北电力大学电气与电子工程学院，北京市 102206
  3.华北电力大学国家能源发展战略研究院，北京市 102206
- 作者简介：
- 基金信息：
  
  Smart Grid-National Science and Technology Major Project(2025ZD0804700)
- DOI：10.7500/AEPS20251126001
  CLC：
- Received：26 November 2025，
  
  Revised：2026-03-25，
  
  Online First：28 July 2026，
  
  Published：10 September 2026
- 稿件说明：
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王鹏,刘文宇,曹雨洁等.合作博弈视角下计算任务调度驱动的算力-电力双向协同优化[J].电力系统自动化,2026,50(17):62-73.

WANG Peng,LIU Wenyu,CAO Yujie,et al.Computing-task-scheduling-driven Bidirectional Coordinated Optimization for Computing Power and Electric Power from Perspective of Cooperative Game[J].Automation of Electric Power Systems,2026,50(17):62-73.
王鹏,刘文宇,曹雨洁等.合作博弈视角下计算任务调度驱动的算力-电力双向协同优化[J].电力系统自动化,2026,50(17):62-73. DOI： 10.7500/AEPS20251126001.

WANG Peng,LIU Wenyu,CAO Yujie,et al.Computing-task-scheduling-driven Bidirectional Coordinated Optimization for Computing Power and Electric Power from Perspective of Cooperative Game[J].Automation of Electric Power Systems,2026,50(17):62-73. DOI： 10.7500/AEPS20251126001.

摘要

数据中心可以通过计算任务调度改变其负荷，将成为新型电力系统中重要的需求侧灵活调节资源。由于数据中心与电力系统的运行目标存在差异、无法完全共享信息等问题，当前仍未形成有效的算力-电力双向协同方式。文中提出一种合作博弈视角下计算任务调度驱动的算力-电力双向协同优化方法。首先，提出了基于纳什谈判理论的电力系统运营商-数据中心运营商双向协同框架，以协调实现双方的效用提升；接着，构建了详细的交互型负载、批处理作业两类计算任务的调度模型，并提出了基于滚动时域优化的计算任务调度决策方法；随后，提出了分布式框架下的算力-电力协同决策在线求解方法，在双方内部运行参数与信息保密的前提下，实现全局最优性和求解实时性的兼顾。算例结果验证了所提方法的有效性。

Abstract

Data centers can adjust their load through computing task scheduling

which will become an important flexible demand-side regulation resource in new power systems. However

data centers and power systems have different operation objectives and cannot fully share information. An effective bidirectional coordination method for computing power and electric power has not yet been established. This paper proposes a bidirectional coordinated optimization method for computing power and electric power driven by computing task scheduling from a cooperative game perspective. First

a bidirectional coordinated optimization framework for data center operators and power system operators is proposed based on the Nash bargaining theory

to coordinate utility improvements for both parties. Next

detailed computing task scheduling models for interactive workloads and batch jobs are established

and a computing task scheduling decision-making method based on rolling horizon optimization is proposed. Subsequently

a distributed online solution method for collaborative decision-making of computing power and electric power is proposed. It balances global optimality and real-time solution efficiency while preserving the confidentiality of internal operation parameters and information of both parties. Case study results verify the effectiveness of the proposed method.

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references

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