基于自适应鲁棒优化的野火易发电力系统大规模韧性规划
Large-Scale Resilience Planning for Wildfire-Prone Electricity-System via Adaptive Robust Optimization
AI总结：
针对野火风险下的电力系统，提出一种联合优化长期基础设施配置与短期运行响应的三阶段鲁棒规划框架，通过数据驱动的不确定集和列与约束生成算法实现大规模求解。
摘要：
野火风险对电力公司构成日益严峻的挑战，因为电力线故障可能引发野火，而大型火灾可能破坏电网运行。电力公司越来越依赖诸如公共安全断电（PSPS）和快速跳闸保护等运行干预措施来降低点火风险，但这些措施如果不加区分地部署，可能导致大范围服务中断。基础设施规划决策——如馈线分段和保护配置——在决定这些干预措施的有效性方面起着关键作用。我们开发了一个野火韧性规划框架，在不确定的点火风险下联合优化长期基础设施配置和短期运行响应。该问题被建模为一个三层优化模型，捕捉基础设施规划、野火风险实现和自适应运行决策之间的相互作用。为了表示系统范围的点火不确定性，我们构建了一个数据驱动的不确定集，结合了段级预测区间和组级不确定性预算。利用模型结构，我们将问题重新表述为一个易于处理的鲁棒优化模型，并开发了一个可扩展的列与约束生成算法。合成实验和一个投资者拥有的公用事业配电系统的大规模案例研究表明，分段和运行缓解策略的协调规划可以在保持服务可靠性的同时显著降低野火风险。
英文摘要：
Wildfire risk poses a growing challenge for electric utilities, as powerline failures can ignite wildfires while large fires can disrupt grid operations. Utilities increasingly rely on operational interventions such as Public Safety Power Shutoffs (PSPS) and fast-trip protection to mitigate ignition risk, but these measures can cause widespread service disruptions if deployed indiscriminately. Infrastructure planning decisions--such as feeder sectionalization and protection configuration--play a key role in determining how effectively these interventions can be targeted. We develop a planning framework for wildfire resilience that jointly optimizes long-term infrastructure configuration and short-term operational response under uncertain ignition risk. The problem is formulated as a tri-level optimization model capturing the interaction between infrastructure planning, wildfire risk realization, and adaptive operational decisions. To represent system-wide ignition uncertainty, we construct a data-driven uncertainty set that combines segment-level prediction intervals with group-level uncertainty budgets. Leveraging the model structure, we reformulate the problem as a tractable robust optimization model and develop a scalable column-and-constraint generation algorithm. Synthetic experiments and a large-scale case study on an investor-owned utility distribution system show that coordinated planning of sectionalization and operational mitigation strategies can substantially reduce wildfire risk while maintaining service reliability.
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