用自适应鲁棒优化提升电力系统抗极端天气能力
Enhancing Electricity-System Resilience with Adaptive Robust Optimization and Conformal Uncertainty Characterization
- 三阶段模型统一规划、威胁应对和应急响应
- 覆盖保证的不确定性集使性能优于传统方法
- 适合电网规划与韧性评估研究者
极端天气正加剧电力系统的压力，暴露出现有被动响应策略的局限性，亟需主动韧性规划。现有方法多采用简化不确定性模型，并将主动规划与应急响应分离。本文提出一种新型三阶段优化模型，整合主动措施、对抗性破坏和被动响应。利用置信预测构建无分布假设的系统扰动不确定性集，具备覆盖率保证。通过对偶理论将三阶段问题转化为双阶段形式，并采用Bender分解求解。数值实验表明，该方法在性能上优于传统鲁棒优化和两阶段方法。
原文摘要 · Abstract (English)
Extreme weather is straining electricity systems, exposing the limitations of reactive responses, and prompting the need for proactive resilience planning. Most existing approaches to enhance electricity system resilience employ simplified uncertainty models and decouple proactive and reactive decisions. This paper proposes a novel tri-level optimization model that integrates proactive actions, adversarial disruptions, and reactive responses. Conformal prediction is used to construct distribution-free system-disruption uncertainty sets with coverage guarantees. The tri-level problem is solved by using duality theory to derive a bi-level reformulation and employing Bender's decomposition. Numerical experiments demonstrate that our approach outperforms conventional robust and two-stage methods.
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