标题： 考虑环境风况的随机经济调度高效情景生成 显示英文标题

标题： Efficient Scenario Generation for Chance-constrained Economic Dispatch Considering Ambient Wind Conditions

摘要： 场景生成是一种有效的数据驱动方法，用于解决机会约束优化问题，同时在有限样本数量下确保所需的风崄保证。 在现实世界中部署此技术时出现的关键挑战是由于缺乏针对特定应用的适当风险调整模型。 在本文中，我们专注于设计用于电力系统经济调度的有效场景生成方案。 我们提出了一种基于利用环境风况过滤场景的新场景生成方法。 这些过滤后的场景被逐步部署，以在使用最少资源的情况下满足所需的风崄水平。 为了研究所提出方案的性能，我们通过实际的风力发电预测数据对24节点和118节点系统进行了案例研究，并展示了该过程。 数值结果表明，所提出的过滤与增量场景生成模型为机会约束经济调度问题提供了一个精确且高效的解决方案。 显示英文摘要

摘要： Scenario generation is an effective data-driven method for solving chance-constrained optimization while ensuring desired risk guarantees with a finite number of samples. Crucial challenges in deploying this technique in the real world arise due to the absence of appropriate risk-tuning models tailored for the desired application. In this paper, we focus on designing efficient scenario generation schemes for economic dispatch in power systems. We propose a novel scenario generation method based on filtering scenarios using ambient wind conditions. These filtered scenarios are deployed incrementally in order to meet desired risk levels while using minimum resources. In order to study the performance of the proposed scheme, we illustrate the procedure on case studies performed for both 24-bus and 118-bus systems with real-world wind power forecasting data. Numerical results suggest that the proposed filter-and-increment scenario generation model leads to a precise and efficient solution for the chance-constrained economic dispatch problem.