A Bi-Level Optimization Model for Inter-Provincial Energy Consumption Transfer Tax in China
The serious energy crisis and environmental problems resulting from fossil energy excessive consumption have caused severe challenges to the control of energy consumption and intensity (dual controls) and the sustainable development of China’s economy and society. The current territorial management...
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Published in: | Energies (Basel) Vol. 16; no. 21; p. 7328 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Basel
MDPI AG
01-11-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | The serious energy crisis and environmental problems resulting from fossil energy excessive consumption have caused severe challenges to the control of energy consumption and intensity (dual controls) and the sustainable development of China’s economy and society. The current territorial management model (TMM) of energy consumption “dual control” needs urgent improvement. Therefore, this study proposes an inter-provincial energy consumption transfer tax model (ECTTM) based on the Stackelberg game and bi-level optimization theory. In this model, the central government is the leader at the upper-level, and provincial governments are the lower-level followers. An optimization algorithm based on NSGA-II was designed to solve this model to obtain the optimal transfer tax rate and provincial energy consumption. The ECTTM aims to maximize the socioeconomic benefits of energy consumption overall and in each province under the premise of achieving the dual control target. The model’s effectiveness and superiority were illustrated through an empirical study of electricity consumption in Shanghai, Zhejiang, Shaanxi, and Guizhou. Compared with the TMM, the socioeconomic benefits under the ECTTM increased by 14.67%, and the electricity consumption per unit of gross domestic product decreased by 12.8%. Policy suggestions on the ECTTM’s implementation are proposed to promote further improvements in dual controls. |
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ISSN: | 1996-1073 1996-1073 |
DOI: | 10.3390/en16217328 |