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• Establishing a dispatch model for integrated wind-photovoltaic-thermal power system. • Dynamic carbon emissions trading system applications in power market is considered. • Comprehensive benefits of five dispatch modes are compared. • Optimal mode was investigated using case study transmission project (China). To transmit renewable energy on-grid over a large-scale power transmission system, an optimal dispatch model for a multi-energy power generation system is essential. This paper proposed a multi-energy hybrid power dispatch model for an integrated wind-photovoltaic-thermal power system. We consider five different dispatch modes and a dynamic carbon emissions trading system. Design of the modes was based on dispatch objectives. Power dispatch was based on interactive planning of power units and carbon emissions trading. To compare the modes, a comprehensive benefit evaluation index for dispatching is established. The proposed model was applied to supporting power supply system of the Tianzhong ultra-high voltage direct-current transmission project in Xinjiang, China. The results confirmed that high-efficiency mode is an optimal dispatch mode for the power transmission system, and has the most significant benefits. The impact on the optimal mode of the renewable energy penetration rate and carbon emissions trading system, as the two main factors, were further investigated. It was found that high-efficiency mode could maximize existing renewable energy generation and reduce coal consumption and carbon emission used for power generation and has a positive effect on carbon reduction. However, initial quotas need to be controlled more strictly than prices. [ABSTRACT FROM AUTHOR]

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age. • A decision-making optimization model of CCPs low-carbon technology is proposed. • A dynamic CET system with upper-lower layer interaction is introduced. • The proposed dynamic CET system results in 27% reduction in total costs. • The high-resolution data of coal power in Beijing-Tianjin-Hebei region are used. • The strategy to solve the conflict between cleanliness and flexibility is given. [ABSTRACT FROM AUTHOR]