Abstract:

Under the dual-carbon goals, achieving the synergistic optimization of economic and environmental benefits in virtual power plants is crucial for the green transformation of the energy system. However, current research still faces two major challenges: the optimization models struggle to balance economic and environmental benefits simultaneously, and the solution methods tend to be conservative with poor convergence. To address these issues, a low-carbon economic dispatch model for virtual power plants incorporating distributed energy storage under a carbon-green certificate trading mechanism is proposed. First, moving beyond the limitations of single trading mechanisms, a risk-aware carbon-green certificate synergistic trading mechanism is constructed to maximize emission reduction revenue and economic benefits. Second, leveraging the advantages of distributed energy storage in enhancing economic efficiency and renewable energy consumption rates, the potential of the carbon-green certificate mechanism is further exploited by establishing a diversified source virtual power plant optimization model that includes distributed storage. Finally, to overcome the conservativeness and poor convergence of traditional solution methods, the black-winged kite algorithm is introduced to improve solving efficiency. Simulation results demonstrate that the proposed model significantly increases the renewable energy consumption rate and net system profit while effectively reducing carbon emissions. Compared to a single carbon trading mechanism, it achieves up to a 33.9% increase in net profit and a 16.6% reduction in carbon emissions, with faster iteration speed and stronger convergence stability, validating the algorithm's effectiveness in handling high-dimensional nonlinear constrained problems.

Key words: virtual power plant, distributed energy storage, economic analysis