Stochastic optimal scheduling strategy of cross-regional carbon emissions trading and green certificate trading market based on Stackelberg game

Under the urgent goal of carbon peaking and carbon neutralization in China and based on the distribution characteristics of renewable energy, it is essential to promote the large-scale consumption of renewable energy and increase the proportion of large-scale renewable energy in market transactions. Therefore, a stochastic optimal scheduling model that combines the Stackelberg game, cross-regional carbon emissions trading, and tradable green certificate transaction to consider the uncertainty of renewable energy power generation is proposed. To encourage more market participants to participate in the tradable green certificate trading, the model uses Stackelberg game theory to analyze the complex interest relationship between different market participants and obtain a scheduling scheme that balances the interests of different participants. To give full play to the role of the trading mechanism on the cross-regional system, the tradable green certificate trading mechanism and the carbon emission trading mechanism are combined to optimize the overall allocation of green certificates and carbon emission rights, to stimulate renewable energy generation, limit the carbon emission of traditional thermal power units and promote energy conversion. Finally, the modified IEEE 39-bus system and Hami power grid (in Western China) are used as examples to illustrate the feasibility and effectiveness of the proposed scheduling model. The results show that the proposed strategy improves the cross-regional system economy and reduces emissions, fully reflects the monetary value of the external characteristics of renewable energy, guides renewable energy investment and power grid planning, and promotes the consumption of renewable energy.

Automated summary

Promoting the large-scale consumption of renewable energy and increasing the proportion of large-scale renewable energy in market transactions is crucial for achieving carbon peaking and carbon neutralization in China. This study proposes a stochastic optimal scheduling model that considers the uncertainty of renewable energy power generation. By using Stackelberg game theory, the model analyzes the complex interest relationship between different market participants and obtains a scheduling scheme that balances the interests of different participants. The model also combines the tradable green certificate trading mechanism and the carbon emission trading mechanism to optimize the overall allocation of green certificates and carbon emission rights, stimulating renewable energy generation and promoting energy conversion.