An-Extended-Robust-Constraints-Based Source-Grid-Load Collaborative Optimization for Operation Flexibility in Micro-Grid

In the research focusing on optimizing the operation of the source-grid-load collaboration, considering the flexibility of the power system, a key challenge to address is the uncertainty modeling problem. This challenge becomes more pressing with the increasing integration of new energy sources into the grid. To address the challenges, this paper combines the strengths of robust optimization and stochastic programming methods. It flexibly adjusts the constraints containing uncertainty factors while ensuring robustness. This approach leads to an optimal scheduling scheme that exhibits both robustness and flexibility. Furthermore, the study analyzes the impact of uncertainty factors and the active regulation resources of the source and load, considering their physical significance. Case studies demonstrate the feasibility and the validity of the proposed method.