发表机构
Princeton University（普林斯顿大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文构建框架分析数据中心电力需求增长与电网供应不足的矛盾，通过确定性模型、随机过程和随机控制方法，揭示负荷预测不确定性和价值蚕食削弱投资激励，导致电价上涨风险。
AI 中文摘要
二十一世纪的变革性技术——人工智能，正日益受到二十世纪变革性技术——电网的制约。数据中心电力需求的快速增长导致电价上涨，而供应侧却缺乏相应的响应。我们开发了一个框架，将数据中心负荷增长、可用发电容量和市场出清价格联系起来，以理解这一现象。我们首先分析一个确定性模型，以展示需求和供应增长率的不同估计如何影响价格。然后，我们将新数据中心的扩张及其相关电力需求，连同新电力供应的建设，建模为随机过程，从而得出供应、需求和价格的概率分布，而非单一预测。最后，我们将发电扩张表述为一个随机控制问题，其中追求收益最大化的投资者动态选择供应侧投资的强度。该分析凸显了数据中心建设的一个核心挑战：即使需求快速增长增加了对新发电能力的需要，与负荷预测、开发执行风险以及过度建设容量导致的价值蚕食相关的不确定性，可能会削弱以维持电价稳定所需的速度进行投资的激励。
英文摘要
The twenty-first century's transformative technology, artificial intelligence, is increasingly constrained by the twentieth century's transformative technology, the electricity grid. Rapid growth in electricity demand from data centers is leading to higher electricity prices, without a compensating supply-side response. We develop a framework linking data-center load growth, available generation capacity, and market-clearing prices to understand this phenomenon. We first analyze a deterministic model to show how differing estimates of demand and supply growth rates affect prices. We then model the expansion of new data centers and their associated electricity demand, together with build-outs of new electricity supply, as stochastic processes,resulting in probabilistic distributions of supply, demand, and prices rather than a single forecast. Finally, we formulate generation expansion as a stochastic control problem in which a revenue-maximizing investor dynamically chooses the intensity of supply-side investments. The analysis highlights a central challenge of the data-center build-out: even when rapid demand growth increases the need for new generation, the uncertainties related to load forecasts, development execution risks, and value cannibalization from overbuilding capacity may weaken incentives to invest at the pace required to keep electricity prices stable.
