论文标题
基于净负载不确定性下的Kullback-Leibler Divergence分配功能强大的单位承诺
Kullback-Leibler Divergence-Based Distributionally Robust Unit Commitment Under Net Load Uncertainty
论文作者
论文摘要
可再生资源深化到电力系统的渗透需要令人满意地克服的巨大困难。值得特别注意的问题是在净负荷不确定性下对电力系统的短期计划。为此，我们制定了一种具有分配强大的单位承诺方法，该方法明确评估与净负荷相关的不确定性。所提出的方法的主要强度在于其代表净负载概率性质而无需阐明其概率分布的能力。这种强度是由歧义集的概念带来的，对于本文采用了kullback-leibler差异的构建。我们使用代表性研究证明了拟议的方法对实际数据的有效性。执行的灵敏度分析为广泛的数组提供了定量答案，如果有关差异耐受性和数据集大小对最佳解决方案的影响的问题。
The deepening penetration of renewable resources into power systems entails great difficulties that have not been surmounted satisfactorily. An issue that merits special attention is the short-term planning of power systems under net load uncertainty. To this end, we work out a distributionally robust unit commitment methodology that expressly assesses the uncertainty associated with net load. The principal strength of the proposed methodology lies in its ability to represent the probabilistic nature of net load without having to set forth its probability distribution. This strength is brought about by the notion of ambiguity set, for the construction of which the Kullback-Leibler divergence is employed in this paper. We demonstrate the effectiveness of the proposed methodology on real-world data using representative studies. The sensitivity analyses performed provide quantitative answers to a broad array of what if questions on the influence of divergence tolerance and dataset size on optimal solutions.
