An Improved Robust SCUC Approach Considering Multiple Uncertainty and Correlation

Abstract

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.