Abstract: In recent years, under the guidance of the "dual carbon" goal, more and more distributed energy sources in China have been integrated into the power grid, which has brought hidden dangers to the overall security of the power grid. As a comprehensive energy network, virtual power plants face challenges such as high actual carbon emissions, insufficient new energy consumption capacity, complex multi energy flow optimization variables, and diverse optimization objectives. To this end, a novel multi-objective optimization scheduling method is proposed, which not only considers carbon capture technology, but also deeply integrates biomass power plants, aiming to improve the consumption capacity of virtual power plants for new energy and significantly reduce carbon emissions. Firstly, based on the actual carbon emissions of virtual power plants, this article constructs a stepped carbon trading mechanism to incentivize virtual power plants to reduce carbon emissions. Subsequently, in order to reduce the operating costs of the energy system and carbon emissions, a dual objective optimization scheduling model was constructed. The core of this model is to find the most suitable optimization solution for operating costs and carbon emissions, ensuring the dual optimization of economic and environmental benefits in the energy scheduling process.To solve this model, the NSGA-II optimization algorithm is adopted, which has strong search ability and optimization performance, making the solving process more efficient and accurate.