Siting Planning Method for Interconnected Data Centers Considering Decision-dependent Uncertainties

DENG Rongnan; SONG Meng; QIAO Lin; XIA Yurui; BAI Wenchao; GAN Wei

doi:10.7500/AEPS20250802002

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Siting Planning Method for Interconnected Data Centers Considering Decision-dependent Uncertainties

更新时间：2026-09-23

- Siting Planning Method for Interconnected Data Centers Considering Decision-dependent Uncertainties
- Automation of Electric Power Systems Pages: 1-15(2026)
- 作者机构：
  
  1.东南大学电气工程学院，江苏省南京市 210096
  2.国网辽宁省电力有限公司信息通信分公司，辽宁省沈阳市 110002
  3.卡迪夫大学工程学院，卡迪夫 CF24 3AA，英国
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2024YFE0209900)
- DOI：10.7500/AEPS20250802002
  CLC：
- Received：02 August 2025，
  
  Revised：2025-12-08，
  
  Online First：05 February 2026，
- 稿件说明：
移动端阅览
邓荣楠,宋梦,乔林等.计及决策依赖不确定性的互联数据中心选址规划方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250802002.

DENG Rongnan,SONG Meng,QIAO Lin,et al.Siting Planning Method for Interconnected Data Centers Considering Decision-dependent Uncertainties[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250802002.
邓荣楠,宋梦,乔林等.计及决策依赖不确定性的互联数据中心选址规划方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250802002. DOI：

DENG Rongnan,SONG Meng,QIAO Lin,et al.Siting Planning Method for Interconnected Data Centers Considering Decision-dependent Uncertainties[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250802002. DOI：

摘要

随着“东数西算”战略的深入实施，数据中心建设规模的快速增长使其选址规划需要更加精细化的考量。文中针对数据中心规划中选址与算力的决策依赖不确定性（DDU），提出了一种互联数据中心两阶段鲁棒优化方法。首先，构建互联数据中心决策依赖预算不确定集，以动态量化数据中心选址决策与算力需求波动的内生关联；然后，基于决策依赖不确定集，建立计及DDU的互联数据中心两阶段鲁棒混合整数规划模型，涵盖土地、设备、电力、碳排放等多维度成本要素；最后，针对传统列与约束生成（CCG）算法无法处理DDU的问题，定制化设计了改进的Benders&CCG算法，以快速精确求解互联数据中心规划的DDU问题。算例结果表明，与传统决策无关不确定性方法相比，所提方法的总成本降低了4.73%，并且在极端场景下仍能保障算力需求。灵敏度分析进一步验证了所提模型对需求波动的强适应性。研究为高资本密集、长周期的互联数据中心规划提供了兼顾经济性与鲁棒性的决策工具，能够进一步助力双碳目标与数字经济协同发展。

Abstract

With the deepening implementation of the “East Data

West Computing” strategy

the rapid growth of data center construction requires more refined site planning. This paper addresses the decision-dependent uncertainty (DDU) in siting and computing power decisions of data center planning

and proposes a two-stage robust optimization method for interconnected data centers. First

a decision-dependent budget uncertainty set is constructed to dynamically quantify the endogenous coupling between data center siting decisions and fluctuations in computing power demand. Then

based on the decision-dependent uncertainty set

a two-stage robust mixed-integer programming model that accounts for DDU is established for interconnected data centers

incorporating multi-dimensional cost components including land

equipment

electricity

and carbon emission. Finally

to overcome the inability of the conventional column-and-constraint generation (CCG) algorithm to handle DDU

an improved Benders&CCG algorithm is custom-designed to rapidly and accurately solve the DDU problem in interconnected data center planning. Case results show that

compared with the conventional decision-independent uncertainty method

the proposed method reduces the total cost by 4.73% while still guaranteeing computing power demand under extreme scenarios. Sensitivity analysis further verifies the strong adaptability of the proposed model to demand fluctuations. This study provides a decision-making tool that balances economic efficiency and robustness for the planning of interconnected data centers

which are characterized by high capital intensity and long planning horizons

and can further support the coordinated development of the carbon-peaking and carbon-neutrality goals and the digital economy.

关键词

Keywords

references

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