Economical Optimization Scheduling of Microgrids Based on Improved Distributionally Robust Optimization

To enhance the microgrid's ability to handle uncertainty and improve overall operational economy, an improved distributionally robust economic optimization scheduling model for microgrids is proposed. Based on the distributionally robust optimization approach, a microgrid optimization scheduling model considering distributed photovoltaic uncertainty is established. The Hausdorff distance is used to improve the probability distribution set in the distributionally robust model. This model optimizes the microgrid scheduling strategy under the worst-case probability distribution scenario, obtaining the optimized scheduling results for each operational unit and conducting a detailed analysis. Example results show that the probability distribution set established using the Hausdorff distance can effectively improve the economic performance of the distributionally robust model, and the model's robustness can be controlled by adjusting the confidence level.