Multi-objective optimal scheduling of virtual power plant considering carbon capture and multi-energy flow

Abstract

As an integrated energy network with multi-energy flow interconnected， virtual power plants （VPPs） face difficulties such as high actual carbon emissions， insufficient new energy consumption capacity， complex optimization variables of multi-energy flow， and non-uniform optimization objectives. To this end， a multi-objective optimal scheduling method for virtual power plants considering carbon capture and multi-energy flow is proposed to improve the new energy consumption capacity of multi-energy flow virtual power plants and reduce carbon emissions. First， a reward and punishment ladder-type carbon trading mechanism is established based on the actual carbon emissions of the virtual power plant. Then， a dual-objective optimal scheduling model is built with the minimization of operating costs and carbon emissions as the objective function and solved by using the multi-objective salp swarm algorithm. Finally， multiple scheduling scenarios are set up to compare and analyze the performance of the multi-objective optimization algorithm. The results verify the feasibility and effectiveness of the optimal scheduling model.

Keywords

• vpp
• carbon capture
• multi-energy flow
• multi-objective salp swarm algorithm
• optimal scheduling