Abstract: The power sector is one of the largest carbon emitters in China and faces nonlinear cost impacts from different emission reduction measures across regions with varying electricity demand characteristics. In this study, we analyze the effects and cost efficiency of supply-side and demand-side emission reduction pathways by classifying Chinese provinces into four categories. This is accomplished through integration of the Next Energy Modeling System for Optimization (NEMO) and the Low Emissions Analysis Platform (LEAP), i.e., LEAP-NEMO. Applying this method, our results show that urbanization will likely drive stable growth in residential electricity demand, while industrial development will vary regionally. Resource-rich regions require wind and solar energy as foundational methods to decarbonize their mix of electricity sources, whereas areas with limited natural resources need nuclear energy and alternative energy generation technologies to mitigate supply gaps. Furthermore, we find that delaying the emission peak year raises marginal carbon reduction costs and the cumulative cost per unit of carbon abatement. A 1.5% reduction in energy intensity is the most cost-effective for the majority of regions.

Key words: Power systems; Low Emissions Analysis Platform-Next Energy Modeling System for Optimization (LEAP-NEMO); Clean energy transition; Energy consumption

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