In this letter, we propose a tractable formulation and an efficient solution method for the Wasserstein-metric-based distributionally robust unit commitment (DRUC-dW) problem. First, a distance-based data aggregation method is introduced to hedge against the dimensionality issue arising from a huge volume of data. Then, we propose a novel cutting plane algorithm to solve the DRUC-dW problem much more efficiently than state-of-the-art. The novel solution method is termed extremal distribution generation, which is an extension of the column-and-constraint generation method to the distributionally robust cases. The feasibility and cost efficiency of the model, and the efficiency of the solution method are numerically validated.

中文翻译：

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使用 Wasserstein 度量的数据驱动的分布式稳健单元承诺：易处理的公式和有效的解决方案方法

在这封信中，我们为基于 Wasserstein 度量的分布式稳健单元承诺 (DRUC-dW) 问题提出了一种易于处理的公式和一种有效的解决方法。首先，引入基于距离的数据聚合方法来对冲海量数据带来的维度问题。然后，我们提出了一种新的切割平面算法，以比最先进的技术更有效地解决 DRUC-dW 问题。这种新的求解方法被称为极值分布生成，它是列约束生成方法对分布鲁棒情况的扩展。数值验证了模型的可行性和成本效率，以及求解方法的效率。