Application of Bayesian-based Distributional Robust Optimization in Wind and Solar Power Output Prediction

In order to clarify the variability of renewable energy generation, this paper proposes using Bayesian multivariate nonlinear models and Bayesian nonlinear interaction models to describe the power uncertainty of wind and solar generation, based on distributionally robust optimization methods. The wind and solar output for typical scenarios are then calculated. Finally, the variations in wind and solar output under different confidence levels are analyzed.