标题： 数据驱动的两阶段分布鲁棒多能源微电网调度 显示英文标题

标题： Data-Driven Two-Stage Distributionally Robust Dispatch of Multi-Energy Microgrid

摘要： 本文研究了多能源微电网在供应和需求不确定性下的自适应分布鲁棒调度（DRD）问题。构建了一个沃塞尔斯坦模糊集来支持数据驱动的决策。通过充分挖掘原始视角下最坏情况期望的特殊结构，定制并开发了一种新颖且高效的列与约束生成框架下的分解算法，以应对计算负担。数值研究表明了我们提出的DRD方法的有效性，并揭示了它与传统基于随机规划和鲁棒优化调度方法之间的相互关系。此外，与文献中两阶段分布鲁棒优化的流行算法相比，验证了我们算法在求解DRD问题上的强大能力。 显示英文摘要

摘要： This paper studies adaptive distributionally robust dispatch (DRD) of the multi-energy microgrid under supply and demand uncertainties. A Wasserstein ambiguity set is constructed to support data-driven decision-making. By fully leveraging the special structure of worst-case expectation from the primal perspective, a novel and high-efficient decomposition algorithm under the framework of column-and-constraint generation is customized and developed to address the computational burden. Numerical studies demonstrate the effectiveness of our DRD approach, and shed light on the interrelationship of it with the traditional dispatch approaches through stochastic programming and robust optimization schemes. Also, comparisons with popular algorithms in the literature for two-stage distributionally robust optimization verify the powerful capacity of our algorithm in computing the DRD problem.