Economic analysis and impact assessment of electricity supply and demand-side emission reductions in China under carbon neutrality goals

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.

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Publication Details

Journal
Journal of Zhejiang University. Science A
Published
2026-02-14
DOI
https://doi.org/10.1631/jzus.a2500160
Primary Topic
Integrated Energy Systems Optimization
Type
article
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article

Economic analysis and impact assessment of electricity supply and demand-side emission reductions in China under carbon neutrality goals

Xinhao Du, Xuanxuan Ming, Qiang Wang, Jianren Fan et al.
Journal of Zhejiang University. Science A
Integrated Energy Systems Optimization
article

Economic analysis and impact assessment of electricity supply and demand-side emission reductions in China under carbon neutrality goals

Xinhao Du, Xuanxuan Ming, Qiang Wang, Jianren Fan, Kun Luo
article en

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.

Journal of Zhejiang University. Science AVol. 27(3)
National Institute of Clean and Low-Carbon Energy (CN), Zhejiang Energy Group (China) (CN), State Key Laboratory of Clean Energy Utilization, Zhejiang University (CN)
Sustainable cities and communities
Openalex Percentile: Top 30%
Integrated Energy Systems Optimization
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