Distributionally robust optimal dispatch modelling of renewable-dominated power system and implementation path for carbon peak

The renewable-dominated power system has a high proportion of renewable generation, which promotes the achievement of the carbon peak and carbon neutrality objectives in the power industry. However, renewable generation is dependent on volatile and unpredictable natural resources. Moreover, the renewable resources and load demands are inversely distributed in some countries such as China. Besides, renewable generation is not in sync with load demands. Therefore, the renewable-dominated power system needs a high proportion of cross-region power transmission and requires more reliable dispatching to maintain the generation/load balance than conventional systems. At first, the renewable-dominated power system is divided into three levels in this paper, the cross-regional transmission level, renewable generation level, and thermal power generation level. A moment uncertainty set is employed to indicate the uncertainty caused by fluctuations in renewable generation. Furthermore, the distributionally robust conditional value-at-risk (DRCVaR) is presented to show the risk of abandoning renewable generation under different weather conditions. Based on the three-level construction and other constraints, a distributionally robust optimal dispatch model is proposed to minimize the carbon emission and the abandonment of renewable generation in the system. Then, the proposed dispatch model is converted into a semidefinite programming problem by the dual optimization theory, which can be easily solved. Finally, the proposed dispatch model is verified with a receiving power system in China. Additionally, the implementation path for the carbon peak of the power industry is proposed. The analysis results show that renewable generation reaches 59% in 2025, and the carbon peak reaches its peak value in 2030. In other words, the carbon peak target can be achieved via the renewable-dominated power system with the proposed dispatch model.

Authors:Bowen Chen, Emmanuel Ackom, Hongming Yang, Junpeng Liu, Sheng Xiang
Published year:2022
Content type:Journal article
Orbit ID:1efe4c3a-6168-4dc3-8fbc-f093adcc6478
Is current:Current
No. of pages:16