发表机构
Dominion Energy（多米尼能源）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对超大规模数据中心带来的负荷增长，本文提出将多粒度负荷预测（含SARIMA、Prophet等模型）纳入长期停电评估，以减少保守性并改善短期停电容纳，支持输电加固与电网现代化。
AI 中文摘要
超大规模数据中心的快速扩张正显著增加北弗吉尼亚地区的电力需求。作为该地区的主要电力公用事业公司，Dominion Energy 必须加强其输电网络以支持这一增长。这些项目需要计划性停电，且必须提前数月进行评估，以支持施工规划和停电协调，同时满足 NERC 和 PJM 的 N-1 可靠性要求。长期停电研究通常按天进行，使用月度或季节性峰值负荷假设。尽管这种方法简化了分析，但可能过于保守，因为它未能捕捉到细粒度的负荷变化。因此，在实际负荷条件下可能可行的短期停电常常被推迟或拒绝，从而延误关键的输电扩建和电网现代化项目。本文评估了将现实的多粒度负荷预测纳入基于事故的长期停电评估中的运行价值，并将结果与传统的基于峰值的方法进行比较。使用统计和机器学习模型（包括 SARIMA、Prophet、梯度提升和随机森林）开发了日、周和月预测，随后进行自下而上的时间协调，以保持各预测时间范围的一致性。结果表明，细粒度负荷预测减少了不必要的保守性，并改善了停电容纳能力，特别是对于短期请求，且不改变现有的可靠性标准。所提出的方法可以加强长期停电协调，并支持及时的输电加固和电网现代化。
英文摘要
The rapid expansion of hyperscale data centers is significantly increasing electricity demand in Northern Virginia. Dominion Energy, the region's primary electric utility, must reinforce its transmission network to support this growth. These projects require planned outages that must be evaluated months in advance to support construction planning and outage coordination while meeting NERC and PJM N-1 reliability requirements. Long-term outage studies are commonly performed day by day using monthly or seasonal peak-load assumptions. Although this approach simplifies analysis, it can be overly conservative because it does not capture granular load variability. Consequently, short-duration outages that may be feasible under realistic loading conditions are often postponed or denied, delaying critical transmission expansion and grid modernization projects. This paper evaluates the operational value of incorporating realistic multigranular load forecasts into long-term, contingency-based outage assessments and compares the results with conventional peak-based methods. Daily, weekly, and monthly forecasts are developed using statistical and machine-learning models, including SARIMA, Prophet, Gradient Boosting, and Random Forest, followed by bottom-up temporal reconciliation to maintain consistency across forecast horizons. Results show that granular load forecasts reduce unnecessary conservatism and improve outage accommodation, particularly for short-duration requests, without changing existing reliability criteria. The proposed approach can strengthen long-term outage coordination and support timely transmission reinforcement and grid modernization.
