发表机构
Electric Power Research Institute (EPRI)（电力研究研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究能源管理系统中 N-1 应急筛选问题，提出审计选择性验证方法，通过廉价替代、在线审计和校准阈值，在任意部署转移下保证热违规率界限，减少全潮流研究，为风险控制提供有效筛选和分类层。
AI 中文摘要
能源管理系统中的实时 N-1 应急筛选需要在保证和成本之间进行权衡：用全潮流验证每个可信停电情况速度太慢，而快速线性灵敏度筛选没有统计保证且可能会使不安全运行点漏检，尤其是当控制器将系统驱动到不熟悉的状态时。本文介绍了审计选择性验证，这是一种用于任何控制器输出（优化、模型预测或学习）的风险预算筛选和分类层。一种廉价的替代方法提出应跳过哪些停电情况；在线审计在每个窗口对一个小的随机样本运行全潮流；并在校准阈值下，以选定的预算和置信度为跳过的集合证明热违规率界限，同时为未验证的可信子集提供相应界限。有效性基于实际验证和审计而非替代方法的准确性，因此在任意部署转移下都成立。它是一种风险预算筛选，当政策要求检查每个可信应急情况时，不能替代确定性验证。在三个多达 1354 条母线的公共输电系统上，实际违规率保持在预算范围内，标准确定性和校准筛选在转移下变得不安全，该方法将每个实时运行点的全潮流研究减少了 29%至 75%。
英文摘要
Real-time N-1 contingency screening in an energy management system trades assurance against cost: verifying every credible outage with full power flow is too slow, while fast linear-sensitivity screening gives no statistical guarantee and can silently pass unsafe operating points, especially when a controller drives the system into unfamiliar regimes. This paper introduces Audited Selective Verification, a risk-budgeted screening and triage layer for any controller's output (optimization, model-predictive, or learned). A cheap surrogate proposes which outages to skip; an online audit runs full power flow on a small random sample each window; and a calibrated threshold certifies a thermal-violation-rate bound for the skipped set at a chosen budget and confidence, with a corresponding bound for the unverified trusted subset. Validity rests on real verification and the audit rather than on surrogate accuracy, so it holds under arbitrary deployment shift. It is a risk-budgeted screen, not a replacement for deterministic verification when policy requires checking every credible contingency. On three public transmission systems up to 1354 buses, the realized violation rate stays within budget, standard deterministic and calibrated screens become unsafe under shift, and the method cuts full power-flow studies by 29 to 75 percent per real-time operating point.
CommentsSubmitted to IEEE Transactions on Power Systems (under review)
