Optimal Scheduling of Virtual Power Plants Under a Multiple Energy Sharing Framework Considering Joint Electricity and Carbon Trading

Abstract

The virtual power plant (VPP) is an excellent approach for mitigating the intermittency and fluctuation of renewable energy sources. The present work proposes an optimal scheduling model for VPPs to leverage the benefits of joint electricity and carbon trading from the perspective of multiple energy-sharing mechanisms. First, the optimal sharing scheduling model of the electric, thermal, and hydrogen energy was established. The model integrates various components, including wind turbines, photovoltaic units, electrolytic cells, combined heat and power units, hydrogen-doped gas boilers, electric energy storage, thermal storage tanks, and hydrogen storage tanks. Then, the model incorporates a tiered carbon trading mechanism to minimize operating and trading costs. Finally, numerical results indicate that, compared with the independent operation of virtual power plants and the lack of joint electricity and carbon trading, the optimal scheduling scheme proposed in this paper reduces the total cost and carbon emissions of the three VPPs by 3.3% and 49.7%, respectively. This demonstrates that the proposed model can effectively reduce the total operating expenses of VPPs by facilitating the allocation of electric, thermal, and hydrogen energy and achieving low-carbon emission operations.