Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model

In this study, we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model, assuming an actual situation with several participants in energy trading. Firstly, the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading. Secondly, the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant. Finally, a combination algorithm of improved robust optimization over time (ROOT) and CPLEX is proposed to solve the established game model. The experimental results indicate that under different fitness thresholds, the robust optimization results of the proposed algorithm are increased by 56.91 % and 68.54 %, respectively. The established bi-level game model effectively balances the benefits of different energy trading entities. The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59 %.