With the large‐scale integration of wind power and photovoltaic power, as well as the rapid development of power systems in recent years, it is of great significance to study meticulous day‐ahead scheduling methods further. A robust security‐constrained unit commitment (SCUC) approach with the considerations of uncertainty outputs and the corresponding probability correlations is proposed in this paper. First, an improved robust SCUC model is constructed according to the multiple uncertainties of outputs and their probability correlations. Then, Cholesky decomposition is used to convert the correlated random samples into independent ones so as to determine the worst scenario directly based on the sample characteristics. Finally, the model is solved by Benders decomposition method. The simulation results based on the IEEE 118‐bus system indicate that the proposed approach can effectively improve the economy while ensuring the robustness of the day‐ahead SCUC decisions under multiple uncertainties. Additionally, the worst scenario determination method based on Cholesky decomposition can effectively promote the compactness of the robust SCUC model and significantly improve the computational efficiency accordingly. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译：

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考虑多重不确定性和相关性的改进鲁棒SCUC方法

随着风电和光伏发电的大规模整合，以及近年来电力系统的飞速发展，进一步研究精细的日前调度方法具有重要的意义。本文提出了一种鲁棒的安全约束单位承诺（SCUC）方法，该方法考虑了不确定性输出和相应的概率相关性。首先，根据输出的多重不确定性及其概率相关性，构建了改进的鲁棒SCUC模型。然后，使用Cholesky分解将相关的随机样本转换为独立样本，从而直接根据样本特征确定最坏的情况。最后，通过Benders分解方法求解模型。基于IEEE 118总线系统的仿真结果表明，所提出的方法可以有效地改善经济性，同时确保在多种不确定性下日间SCUC决策的鲁棒性。此外，基于Cholesky分解的最坏情况确定方法可以有效地提高鲁棒SCUC模型的紧凑性，从而显着提高计算效率。©2020日本电气工程师学会。由Wiley Periodicals LLC发布。基于Cholesky分解的最坏情况确定方法可以有效地提高鲁棒SCUC模型的紧凑性，从而显着提高计算效率。©2020日本电气工程师学会。由Wiley Periodicals LLC发布。基于Cholesky分解的最坏情况确定方法可以有效地提高鲁棒SCUC模型的紧凑性，从而显着提高计算效率。©2020日本电气工程师学会。由Wiley Periodicals LLC发布。