IDEAS home Printed from
   My bibliography  Save this article

Effects of carbon and environmental tax on power mix planning - A case study of Hebei Province, China


  • Wang, B.
  • Liu, L.
  • Huang, G.H.
  • Li, W.
  • Xie, Y.L.


The growing energy crisis and severe atmospheric pollution have put much pressure on the Chinese government and resulted in a lot of revolutionary changes. Considering the upcoming new environmental and carbon tax, how would the tax reform affect the power sector; which types and how much of the different power generation technologies would be added are important questions that need to be answered by decision makers. In this study, a deterministic optimization model is proposed for determining the optimal power mix through the introduction of environmental and carbon taxes. A case study of Hebei Province in China is provided to illustrate the effects of these two taxes. The capacity additions of different generation technologies, air pollutants and CO2 emission amounts, system costs, and regional power security under different tax levels are profoundly examined. The modeling results indicate that such tax policies could significantly improve to the power mix adjustment as well as the quality of the ambient air quality. Higher tax levels would promote the development of renewable power generation. Meanwhile, different degrees of CO2 and air pollutant emission reduction can be achieved. The modeling results could help the decision makers identify the satisfactory tax levels in the future.

Suggested Citation

  • Wang, B. & Liu, L. & Huang, G.H. & Li, W. & Xie, Y.L., 2018. "Effects of carbon and environmental tax on power mix planning - A case study of Hebei Province, China," Energy, Elsevier, vol. 143(C), pages 645-657.
  • Handle: RePEc:eee:energy:v:143:y:2018:i:c:p:645-657
    DOI: 10.1016/

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Xie, Kaigui & Dong, Jizhe & Singh, Chanan & Hu, Bo, 2016. "Optimal capacity and type planning of generating units in a bundled wind–thermal generation system," Applied Energy, Elsevier, vol. 164(C), pages 200-210.
    2. Hui, Jingxuan & Cai, Wenjia & Wang, Can & Ye, Minhua, 2017. "Analyzing the penetration barriers of clean generation technologies in China’s power sector using a multi-region optimization model," Applied Energy, Elsevier, vol. 185(P2), pages 1809-1820.
    3. Zhang, Ning & Hu, Zhaoguang & Shen, Bo & He, Gang & Zheng, Yanan, 2017. "An integrated source-grid-load planning model at the macro level: Case study for China's power sector," Energy, Elsevier, vol. 126(C), pages 231-246.
    4. Hemmati, Reza & Saboori, Hedayat & Siano, Pierluigi, 2017. "Coordinated short-term scheduling and long-term expansion planning in microgrids incorporating renewable energy resources and energy storage systems," Energy, Elsevier, vol. 134(C), pages 699-708.
    5. Muis, Z.A. & Hashim, H. & Manan, Z.A. & Taha, F.M. & Douglas, P.L., 2010. "Optimal planning of renewable energy-integrated electricity generation schemes with CO2 reduction target," Renewable Energy, Elsevier, vol. 35(11), pages 2562-2570.
    6. Guo, Zheng & Ma, Linwei & Liu, Pei & Jones, Ian & Li, Zheng, 2016. "A multi-regional modelling and optimization approach to China's power generation and transmission planning," Energy, Elsevier, vol. 116(P2), pages 1348-1359.
    7. Dong, Huijuan & Dai, Hancheng & Geng, Yong & Fujita, Tsuyoshi & Liu, Zhe & Xie, Yang & Wu, Rui & Fujii, Minoru & Masui, Toshihiko & Tang, Liang, 2017. "Exploring impact of carbon tax on China’s CO2 reductions and provincial disparities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 596-603.
    8. Bildirici, Melike E. & Gökmenoğlu, Seyit M., 2017. "Environmental pollution, hydropower energy consumption and economic growth: Evidence from G7 countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 68-85.
    9. Wierzbowski, Michal & Lyzwa, Wojciech & Musial, Izabela, 2016. "MILP model for long-term energy mix planning with consideration of power system reserves," Applied Energy, Elsevier, vol. 169(C), pages 93-111.
    10. Chen, Qixin & Kang, Chongqing & Xia, Qing & Guan, Dabo, 2011. "Preliminary exploration on low-carbon technology roadmap of China’s power sector," Energy, Elsevier, vol. 36(3), pages 1500-1512.
    11. Zhu, Lei & Fan, Ying, 2010. "Optimization of China's generating portfolio and policy implications based on portfolio theory," Energy, Elsevier, vol. 35(3), pages 1391-1402.
    12. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Kopanos, Georgios M. & Pistikopoulos, Efstratios N. & Georgiadis, Michael C., 2014. "A spatial multi-period long-term energy planning model: A case study of the Greek power system," Applied Energy, Elsevier, vol. 115(C), pages 456-482.
    13. Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian, 2015. "A multi-region optimization planning model for China’s power sector," Applied Energy, Elsevier, vol. 137(C), pages 413-426.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Noussan, Michel, 2018. "Performance based approach for electricity generation in smart grids," Applied Energy, Elsevier, vol. 220(C), pages 231-241.
    2. Lin, Boqiang & Jia, Zhijie, 2019. "How does tax system on energy industries affect energy demand, CO2 emissions, and economy in China?," Energy Economics, Elsevier, vol. 84(C).
    3. Wu, C.B. & Guan, P.B. & Zhong, L.N. & Lv, J. & Hu, X.F. & Huang, G.H. & Li, C.C., 2020. "An optimized low-carbon production planning model for power industry in coal-dependent regions - A case study of Shandong, China," Energy, Elsevier, vol. 192(C).
    4. Freire-González, Jaume & Puig-Ventosa, Ignasi, 2019. "Reformulating taxes for an energy transition," Energy Economics, Elsevier, vol. 78(C), pages 312-323.
    5. Quiroga, Daniela & Sauma, Enzo & Pozo, David, 2019. "Power system expansion planning under global and local emission mitigation policies," Applied Energy, Elsevier, vol. 239(C), pages 1250-1264.
    6. Pinglin He & Jing Ning & Zhongfu Yu & Hao Xiong & Huayu Shen & Hui Jin, 2019. "Can Environmental Tax Policy Really Help to Reduce Pollutant Emissions? An Empirical Study of a Panel ARDL Model Based on OECD Countries and China," Sustainability, MDPI, Open Access Journal, vol. 11(16), pages 1-32, August.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:143:y:2018:i:c:p:645-657. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.