数据中心承载人工智能工作负载引起的电力系统强迫振荡
Forced Oscillations in Power Systems Induced by Data Centers Hosting AI Workloads
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中文总结 AI 辅助
本文研究大型数据中心承载AI工作负载引发的功率摆动对电力系统强迫振荡的风险，通过传递函数识别关键位置，分析失稳类型及谐波影响，为运营商制定负荷波动限制提供依据。
中文摘要 AI 辅助
运行人工智能（AI）工作负载的大型数据中心（DTCs）中的功率摆动可能激发电力系统中阻尼不良的模态。由此产生的强迫振荡可能导致闪变、设备断开或停电。本文研究了在不同系统强度和阻尼条件下此类负荷波动的风险。采用基于传递函数的解析方法，我们识别了电网中关键的数据中心位置，在这些位置负荷波动可能引发最大的强迫振荡，并进一步表征了系统响应的谐波频谱。根据数据中心负荷波动的频率和幅值，强迫振荡可能变得无界。潜在的失稳被分类为强迫周期响应的鞍结分岔和阻抗面遭遇，使用Floquet乘子和代数雅可比矩阵的最小奇异值。此外，分析了方波负荷曲线中不同占空比和基波振荡频率之外的谐波分量的影响。最后，研究了两个振荡数据中心在不同位置和强迫频率下的相互作用，考虑了同步和非同步运行。研究结果可以帮助系统运营商针对特定电网位置的数据中心设施定义最大允许负荷波动的新规定，而不会对系统的稳定性和运行产生负面影响。
英文摘要
Power swings in large Data Centers (DTCs) running Artificial Intelligence (AI) workloads can excite poorly damped modes in power systems. The resulting forced oscillations can lead to flicker, equipment disconnection, or blackouts. This paper investigates the risks of such load fluctuations for different system strengths and damping conditions. Using an analytical approach based on transfer functions, we identify critical DTC locations in the power grid at which load fluctuations could induce the largest forced oscillations and further characterize the harmonic spectrum of the resulting system response. Depending on the frequency and magnitude of the DTC load fluctuations, forced oscillations can become unbounded. The underlying instabilities are classified into saddle-node bifurcations of the forced periodic response and impasse-surface encounters, using Floquet multipliers and the minimum singular value of the algebraic Jacobian. Furthermore, the impact of different duty cycles and harmonic components beyond the fundamental oscillation frequency in square-wave load profiles is analyzed. Finally, the interaction of two oscillating DTCs is investigated for different locations and forcing frequencies, considering both synchronized and unsynchronized operation. The findings can help system operators to define new regulations on the maximum load fluctuations permitted for DTC facilities at specific grid locations, without negatively affecting the stability and operation of the system.
发表机构
- ETH Zurich（苏黎世联邦理工学院）
- University of Toronto（多伦多大学）
机构由 AI 辅助整理，请以论文原文为准。
