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Emission-Intensity-Based Carbon Tax and Its Impact on Generation Self-Scheduling

Author

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  • Ping Che

    (Department of Mathematics, College of Sciences, Northeastern University, Shenyang 110819, China)

  • Yanyan Zhang

    (Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang 110819, China)

  • Jin Lang

    (Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang 110819, China)

Abstract

We propose an emission-intensity-based carbon-tax policy for the electric-power industry and investigate the impact of the policy on thermal generation self-scheduling in a deregulated electricity market. The carbon-tax policy is designed to take a variable tax rate that increases stepwise with the increase of generation emission intensity. By introducing a step function to express the variable tax rate, we formulate the generation self-scheduling problem under the proposed carbon-tax policy as a mixed integer nonlinear programming model. The objective function is to maximize total generation profits, which are determined by generation revenue and the levied carbon tax over the scheduling horizon. To solve the problem, a decomposition algorithm is developed where the variable tax rate is transformed into a pure integer linear formulation and the resulting problem is decomposed into multiple generation self-scheduling problems with a constant tax rate and emission-intensity constraints. Numerical results demonstrate that the proposed decomposition algorithm can solve the considered problem in a reasonable time and indicate that the proposed carbon-tax policy can enhance the incentive for generation companies to invest in low-carbon generation capacity.

Suggested Citation

  • Ping Che & Yanyan Zhang & Jin Lang, 2019. "Emission-Intensity-Based Carbon Tax and Its Impact on Generation Self-Scheduling," Energies, MDPI, vol. 12(5), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:777-:d:209163
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    1. Gerbelová, Hana & Amorim, Filipa & Pina, André & Melo, Mário & Ioakimidis, Christos & Ferrão, Paulo, 2014. "Potential of CO2 (carbon dioxide) taxes as a policy measure towards low-carbon Portuguese electricity sector by 2050," Energy, Elsevier, vol. 69(C), pages 113-119.
    2. Soroudi, Alireza, 2013. "Robust optimization based self scheduling of hydro-thermal Genco in smart grids," Energy, Elsevier, vol. 61(C), pages 262-271.
    3. Timothy Considine & Donald F. Larson, 2012. "Short Term Electric Production Technology Switching Under Carbon Cap and Trade," Energies, MDPI, vol. 5(10), pages 1-21, October.
    4. Alton, Theresa & Arndt, Channing & Davies, Rob & Hartley, Faaiqa & Makrelov, Konstantin & Thurlow, James & Ubogu, Dumebi, 2014. "Introducing carbon taxes in South Africa," Applied Energy, Elsevier, vol. 116(C), pages 344-354.
    5. Lin, Boqiang & Li, Xuehui, 2011. "The effect of carbon tax on per capita CO2 emissions," Energy Policy, Elsevier, vol. 39(9), pages 5137-5146, September.
    6. Rong, Aiying & Lahdelma, Risto, 2007. "CO2 emissions trading planning in combined heat and power production via multi-period stochastic optimization," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1874-1895, February.
    7. Jonathan F. Bard, 1988. "Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation," Operations Research, INFORMS, vol. 36(5), pages 756-766, October.
    8. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
    9. Wei Wei & Yile Liang & Feng Liu & Shengwei Mei & Fang Tian, 2014. "Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach," Energies, MDPI, vol. 7(4), pages 1-18, April.
    10. Weng, Qingqing & Xu, He, 2018. "A review of China’s carbon trading market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 613-619.
    11. Johnson, Kenneth C., 2010. "A decarbonization strategy for the electricity sector: New-source subsidies," Energy Policy, Elsevier, vol. 38(5), pages 2499-2507, May.
    12. Kara, M. & Syri, S. & Lehtila, A. & Helynen, S. & Kekkonen, V. & Ruska, M. & Forsstrom, J., 2008. "The impacts of EU CO2 emissions trading on electricity markets and electricity consumers in Finland," Energy Economics, Elsevier, vol. 30(2), pages 193-211, March.
    13. Zhang, Kun & Wang, Qian & Liang, Qiao-Mei & Chen, Hao, 2016. "A bibliometric analysis of research on carbon tax from 1989 to 2014," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 297-310.
    14. Zhang, Lirong & Li, Yakun & Jia, Zhijie, 2018. "Impact of carbon allowance allocation on power industry in China’s carbon trading market: Computable general equilibrium based analysis," Applied Energy, Elsevier, vol. 229(C), pages 814-827.
    15. Nathaniel O. Keohane, 2009. "Cap and Trade, Rehabilitated: Using Tradable Permits to Control U.S. Greenhouse Gases," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 3(1), pages 42-62, Winter.
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    Cited by:

    1. Wen-Hsien Tsai, 2020. "Carbon Emission Reduction—Carbon Tax, Carbon Trading, and Carbon Offset," Energies, MDPI, vol. 13(22), pages 1-7, November.
    2. Rufaro Garidzirai, 2020. "Time Series Analysis of Carbon Dioxide Emission, Population, Carbon Tax and Energy use in South Africa," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 353-360.

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