Distributed Robust Optimization Scheduling of Integrated Energy System Considering Carbon-Green Certificate Joint Trading

In response to the multiple uncertain challenges faced in the low-carbon transformation of the new power system, this paper constructs a distributed robust optimization scheduling model that takes into account the carbon green certificate joint trading mechanism. Firstly, by introducing a carbon green certificate joint trading mechanism, the consumption of renewable energy can be increased, while also improving the economic efficiency of the system. Secondly, a two-stage distribution robust optimization method based on data-driven approach is proposed to address the uncertainty of wind and solar power output. The initial scene is obtained through Latin hypercube sampling, and then the improved k-means clustering algorithm is used to cluster typical scenes and their corresponding probability distributions. The comprehensive norm is used to constrain the confidence interval, and the column and constraint generation algorithm is used for solving. Finally, a numerical simulation analysis is conducted to verify that the proposed model can promote the consumption of new energy while ensuring the economic efficiency of system operation.