美国互联并网排队系统：级联脆弱性分析与韧性工程框架
The U.S. Interconnection Queue System: Cascading Vulnerability Analysis and a Resilience Engineering Framework
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中文总结 AI 辅助
针对美国并网排队系统撤出级联风险，采用网络传染模型与统计检验，揭示成本分摊设计决定其脆弱性，并提出限制再分配以增强韧性。
中文摘要 AI 辅助
截至2025年，美国互联并网排队（即新建发电和储能项目的电网接入网关）中约有8,200个项目，总容量达2,061吉瓦。2000年至2020年间排队的容量中，仅有13%（按项目数量计为19%）已投入运营。我们认为，排队架构容易因重新研究和成本重新分配而引发自我强化的项目撤出级联，这与研究延迟无关。借鉴金融和相互依赖的基础设施网络中的故障传染模型，我们将排队系统建模为一个复杂自适应系统，并通过以下方式对其进行检验：对七个ISO/RTO的撤出时间聚类和共同撤出进行统计分析，以及一个带有断路器干预的成本分摊相互依赖关系的风格化网络传染模拟。利用截至2025年的LBNL项目级数据，我们发现时间聚类现象（离散指数为5.0至102.4；p<0.001），并识别出39个月度撤出爆发，其中最大的聚类日期事件达到区域均值的67.4倍。在所有七个区域中，撤出时间在技术类别内集中（1,000次置换检验；z=2.58至4.78，p≤0.005）。同期群内的共同撤出仅在四个区域显著（0.5至1.8个百分点）。该模型在低至中等连通性（平均网络度k=3至10）下产生1.0至1.5倍的净级联放大效应。在k=20时，出现类似相变的系统性不稳定转变，在10%冲击下放大效应超过8.7倍（级联规模达97.7%）；这是风格化网络的一个边界条件，在按比例重新分配下消失。与不干预相比，限制每个邻居的成本重新分配可将级联幅度降低最多20%，且每个邻居的平均转移量降低44%。这些发现将互联并网排队系统定性为具有级联脆弱性的关键基础设施，其严重程度取决于成本分配设计。
英文摘要
As of 2025, the U.S. interconnection queues, the grid-access gateway for new generation and storage, contain roughly 8,200 projects totaling 2,061 GW of capacity. Only 13% of capacity queued in 2000-2020 (19% by project count) has reached operation. We argue that the queue architecture is vulnerable to self-reinforcing project withdrawal cascades arising from restudy and cost reallocation, independent of study delays. Adapting failure contagion models from financial and interdependent infrastructure networks, we model the queue as a complex adaptive system and test it with a statistical analysis of withdrawal temporal clustering and co-withdrawal across seven ISO/RTOs and a stylized network contagion simulation of cost-sharing interdependencies with circuit-breaker interventions. Using LBNL project-level data through 2025, we find temporal clustering (dispersion indices 5.0-102.4; p < 0.001) and identify 39 monthly withdrawal bursts with the largest cluster-dated, reaching 67.4x the regional mean. Withdrawal timing is concentrated within technology categories in all seven regions (1,000-permutation test; z = 2.58-4.78, p <= 0.005). Co-withdrawal within cohorts is significant only in four regions (0.5-1.8 percentage points). The model yields net cascade amplification of 1.0-1.5x at low-to-moderate connectivity (average network degree k = 3-10). At k = 20 a phase-transition-like shift to systemic instability occurs, exceeding 8.7x amplification at a 10% shock (97.7% cascade size); a boundary condition of the stylized network that disappears under pro-rata redistribution. Capping per-neighbor cost reallocation reduces cascade magnitude by up to 20% relative to no intervention, with a 44% lower mean per-neighbor transfer. These findings characterize the interconnection queue as critical infrastructure with cascading vulnerability whose severity is conditional on cost allocation design.
发表机构
- Colorado State University（科罗拉多州立大学）
机构由 AI 辅助整理，请以论文原文为准。
