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The existing literature demonstrates that the multi-energy combined power-dispatching system is crucial for resolving the mismatch between the installed capacity and the power generation through renewable energy. However, our knowledge of the impact mechanism of climate policies on this system is still limited. To address this gap, cost-accounting models that consider price fluctuation based on carbon emissions trading and renewable portfolio standards in China are proposed and applied to the integrated wind–photovoltaic–thermal power-dispatching system in Xinjiang. The scenarios analysis showed that in terms of reducing emissions, carbon emissions trading is more effective in cases with a high installed proportion of renewable power, whereas renewable portfolio standards are the opposite, as they are better in two cases in terms of energy saving. The sensitivity analysis indicates that the effect of renewable portfolio standards on the penetration rate of renewable power is constant. There is some potential for the design optimization of these two policies in China, and the characteristics of the power structure should be considered. These results can help the dispatching department in evaluating the impact of carbon emissions trading and renewable portfolio standards to optimize the dispatching strategy and provide directions for policy makers to improve the design. • Explore the interaction of carbon emissions trading and renewable portfolio standards. • Build costs accounting models for climate policies based on fluctuating price. • Analyze the dual effect of the policies in different hybrid power dispatching systems. • Propose policy recommendations to promote the application of policies in China. [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]

At present, vigorously developing wind power, photovoltaic and other renewable energy has become one of the effective ways to deal with carbon dioxide emissions and energy supply and demand gap. Bringing renewable energy into the optimal configuration of power supply structure and reducing carbon emissions at the root will help promote the construction of clean, low-carbon, safe and efficient modern energy system. Therefore, starting from the theory of low-carbon economy, based on the traditional power planning model, this paper considers various uncertainties, introduces social welfare theory, and proposes the optimization scheme of thermal-solar-wind power system. The model is then applied to Southern Xinjiang supporting power project to study the investment behavior of low-carbon power, and the optimal low-carbon power decision-making behavior considering social benefits based on welfare is obtained. The results show that the proposed optimal configuration scheme of hybrid power can achieve the equilibrium between economic and social benefits, improve energy utilization efficiency and provide decision-making reference for policy makers. • A multi-objective power planning optimization model considering social benefits and economic cost was proposed. • Multi-uncertainty and interactions among multiple random variables were examined. • Solutions of various scenarios and different credibility levels were analyzed. • The optimization model can achieve better economic benefits while improving energy efficiency. [ABSTRACT FROM AUTHOR]