Abstract: Under the dual carbon target, the interaction between energy systems and transportation systems will continue to deepen, and there is a collaborative optimization scheduling problem of multiple energy-transportation systems. Therefore, a collaborative optimization scheduling method of electric-gas-thermal multi-energy systems under energy-transportation integration is proposed. Firstly, based on the K-means clustering algorithm fused with DBSCAN and Dijkstra algorithm, the clustering analysis of the scheduled traffic vehicles was carried out, and the road network structure and the energy transfer mode of vehicle operation and Vehicle to Network (V2G) technology were modeled. The traffic objects were electric vehicles and natural gas vehicles. On this basis, a twolevel optimization scheduling model was constructed with the goal of minimizing the total system cost and the total power load fluctuation. Finally, through the numerical example analysis, the effectiveness of the model in reducing system cost, reducing carbon emissions, improving scenery absorption capacity and the superiority of multi-energy system scheduling are verified.

Key words: energy-transportation integration system, bilevel optimization, electric-gas-thermal multi-energy system