电网与AI数据中心隐私保护协调运行：一种检查点感知的三阶段方案
Privacy-Preserving Coordinated Operation of Power Grids and AI Data Centers: A Checkpoint-Aware Three-Phase Scheme
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中文总结 AI 辅助
针对AI数据中心检查点引起的功率波动，提出电网与AIDC间三阶段隐私保护协调方案，通过安全区域认证和检查点感知鲁棒OPF实现安全协调。
中文摘要 AI 辅助
大型语言模型训练和服务的快速增长正推动AI数据中心（AIDC）迈向吉瓦级规模。与传统商业负荷不同，AIDC通过训练和推理工作负载的动态电压频率调整（DVFS）拥有显著运行灵活性，而周期性模型检查点操作可能引发突然的功率下降和反弹，这会侵蚀运行备用容量并增加输电拥堵风险。在这些独特运行特性下，协调AIDC运行与电网调度颇具挑战性，因为电网和AIDC运营商通常不愿共享专有数据和决策权。本文提出了一种电网与AIDC之间的分层隐私保护协调运行方案以解决这一差距。所提方案包含三个阶段。在第一阶段，电网运营商计算AIDC安全区域的认证内近似，用于后续协调。在第二阶段，AIDC运营商协调训练和推理AIDC，在认证安全区域内优化工作负载分配，并生成功率计划和检查点警报。在第三阶段，电网运营商求解考虑可再生能源和检查点不确定性的检查点感知两阶段鲁棒最优潮流（OPF）。通过仅交换紧凑的接口信息，该框架保护了电网和AIDC双方的隐私，避免了频繁的迭代通信，并在保证可行性的前提下实现安全协调。在改进的IEEE 14节点系统和改进的NYISO系统上的数值研究证明了所提框架的有效性、鲁棒性和安全性。
英文摘要
The rapid growth of large language model training and serving is driving AI data centers (AIDCs) toward gigawatt scale. Unlike conventional commercial loads, AIDCs possess significant operational flexibility through dynamic voltage and frequency scaling (DVFS) of training and inference workloads, while periodic model checkpointing can induce abrupt power drops and rebounds that erode operating reserves and increase transmission congestion risks. Coordinating AIDC operation with grid scheduling under these unique operational characteristics is challenging because grid and AIDC operators are generally unwilling to share proprietary data and decision-making authority. This paper proposes a hierarchical privacy-preserving coordinated operation scheme between the power grid and AIDCs to address this gap. The proposed scheme contains three phases. In Phase I, the grid operator computes a certified inner approximation of the AIDCs security region for subsequent coordination. In Phase II, the AIDC operator coordinates training and inference AIDCs to optimize workload allocation within the certified security region and generate power schedules and checkpoint alerts. In Phase III, the grid operator solves a checkpoint-aware two-stage robust optimal power flow (OPF) considering renewable generation and checkpoint uncertainties. By exchanging only compact interface information, the framework preserves the privacy of both grid and AIDCs, avoids frequent iterative communication, and enables secure coordination with guaranteed feasibility. Numerical studies on a modified IEEE 14-bus system and a modified NYISO system demonstrate the effectiveness, robustness, and security of the proposed framework.
发表机构
- The University of Hong Kong（香港大学）
机构由 AI 辅助整理，请以论文原文为准。
