A bi-level multi-objective optimization model for inter-provincial carbon emissions transfer tax on electricity production

Lijun Zeng, Lingyi Guo and Liwen Jiang

Applied Energy, 2024, vol. 356, issue C, No S0306261923017968

Abstract: Low-carbon electricity development is crucial for achieving China's carbon peaking and carbon neutrality goals. The current carbon reduction territorial management model (CRTMM) can only bring short-term carbon reduction and is not enough to motivate provinces to further reduce carbon. However, few studies focus on the inter-provincial coordinated electricity carbon reduction. To overcome the shortcomings of the CRTMM and fill the research gap, this study creatively presents an original bi-level multi-objective inter-provincial carbon emissions transfer tax model (CETTM) on electricity generation in China, where the central government is the upper-level decision maker (leader) and provincial governments are the lower-level decision makers (followers). As the leader, the central government pursues overall maximum economic benefit and minimum pollutant emissions, and as the followers, provincial governments endeavor to maximize internal economic benefits. To ensure the scientificity and accuracy of the calculation results, an improved NSGA-II algorithm is designed to solve the model. Data from Anhui, Qinghai, Heilongjiang, and Jiangsu provinces are then used for empirical analysis to validate the model. The findings demonstrate that the CETTM is superior to the CRTMM in reducing carbon emissions, lowering pollutant emissions and improving economic benefits. The CETTM reduces CO2 emissions by 20.04 × 106 tons, lowers pollutant emissions by 10.65 × 104 tons, and increases benefits by 101.99 × 108 CNY in contrast to the CRTMM. The robustness of the model is verified using a sensitivity analysis. Finally, this study proposes policy recommendations for the CETTM implementation.

Keywords: Transfer tax; Electricity production; Stackelberg game; Carbon emissions (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.apenergy.2023.122432

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