Abstract: This study aims to handle fluctuations in renewable energy effectively and achieve low-carbon, economic, and robust balance optimization in an integrated energy system. A two-stage robust optimization low-carbon economic dispatch model for a park-level integrated energy system that considers carbon trade was proposed. First, an integrated energy system model with carbon capture and storage was constructed. Next, the adjustable uncertainty set was used to describe the fluctuations of wind and photovoltaic output, and a two-stage robust optimization dispatch model was developed with the optimal objective of solving the minimum cost under the worst-case scenario. Subsequently, the column-and-constraint generation algorithm was employed to iteratively solve. Finally, the carbon trading cost was considered in the dispatch model, which limited electricity purchases in the system to reduce indirect carbon emissions and avoid overconservative dispatching schemes. The results show that the two-stage robust optimization method can effectively improve the ability of the system to resist risks and reduce economic loss, and the introduction of a carbon trading mechanism can prevent excessive robustness and maintain low-carbon operation. The proposed method can effectively achieve robust, economical, and low-carbon-balance optimal scheduling for the system.