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Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model

Author

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  • Siqin Xiong

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Yushen Tian

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Junping Ji

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Xiaoming Ma

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

Abstract

To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA) model and a zero-sum game theory (ZSG), this paper constructs a weighted zero-sum game data envelopment analysis (ZSG-DEA) model to allocate the energy consumption quota. Additionally, this paper compares the results with the current administrative targets, to examine the efficiency and feasibility of each allocation mechanism. Finally, this paper employs the proposed model to determine the optimal energy structure for each province in China. The results indicate that by 2020, the national goal of energy structure adjustment will be realized, and energy structure will be diversified in most regions, whereas the coal-dominated status in primary energy consumption will not change. Additionally, the weighted ZSG-DEA model focuses on allocation efficiency while the government considers more regional economic disparity. Therefore, this study suggests a mixture of the two allocation mechanisms in accordance with specific conditions.

Suggested Citation

  • Siqin Xiong & Yushen Tian & Junping Ji & Xiaoming Ma, 2017. "Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model," Sustainability, MDPI, vol. 9(11), pages 1-12, November.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:2115-:d:119392
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    References listed on IDEAS

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    1. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    2. Wen Guo & Tao Sun & Hongjun Dai, 2017. "Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model," Sustainability, MDPI, vol. 9(2), pages 1-18, January.
    3. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    4. Shihong Zeng & Jiuying Chen, 2016. "Forecasting the Allocation Ratio of Carbon Emission Allowance Currency for 2020 and 2030 in China," Sustainability, MDPI, vol. 8(7), pages 1-28, July.
    5. Foo, Dominic C.Y. & Tan, Raymond R. & Ng, Denny K.S., 2008. "Carbon and footprint-constrained energy planning using cascade analysis technique," Energy, Elsevier, vol. 33(10), pages 1480-1488.
    6. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    7. Park, Ji-Won & Kim, Chae Un & Isard, Walter, 2012. "Permit allocation in emissions trading using the Boltzmann distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4883-4890.
    8. Wang, Ke & Zhang, Xian & Wei, Yi-Ming & Yu, Shiwei, 2013. "Regional allocation of CO2 emissions allowance over provinces in China by 2020," Energy Policy, Elsevier, vol. 54(C), pages 214-229.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    11. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    12. Ji-Won Park & Chae Un Kim & Walter Isard, 2011. "Permit Allocation in Emissions Trading using the Boltzmann Distribution," Papers 1108.2305, arXiv.org, revised Mar 2012.
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    Cited by:

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    2. Han, Rong & Li, Jianglong & Guo, Zhi, 2022. "Optimal quota in China's energy capping policy in 2030 with renewable targets and sectoral heterogeneity," Energy, Elsevier, vol. 239(PA).
    3. Jiekun Song & Rui Chen & Xiaoping Ma, 2021. "Collaborative Allocation of Energy Consumption, Air Pollutants and CO 2 Emissions in China," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    4. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    5. Fei Ye & Lixu Li & Zhiqiang Wang & Yina Li, 2018. "An Asymmetric Nash Bargaining Model for Carbon Emission Quota Allocation among Industries: Evidence from Guangdong Province, China," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    6. Wei Yang & Zudi Lu & Di Wang & Yanmin Shao & Jinfeng Shi, 2020. "Sustainable Evolution of China’s Regional Energy Efficiency Based on a Weighted SBM Model with Energy Substitutability," Sustainability, MDPI, vol. 12(23), pages 1-22, December.
    7. Jianguo Zhou & Yushuo Li & Xuejing Huo & Xiaolei Xu, 2019. "How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?," Sustainability, MDPI, vol. 11(3), pages 1-21, February.

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