IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v41y2012icp173-183.html
   My bibliography  Save this article

A multi-period superstructure optimisation model for the optimal planning of China's power sector considering carbon dioxide mitigation

Author

Listed:
  • Zhang, Dongjie
  • Ma, Linwei
  • Liu, Pei
  • Zhang, Lili
  • Li, Zheng

Abstract

Power sector is the largest CO2 emitter in China. To mitigate CO2 emissions for the power sector is a tough task, which requires implementation of targeted carbon mitigation policies. There might be multiple forms for carbon mitigation policies and it is still unclear which one is the best for China. Applying a superstructure optimisation model for optimal planning of China's power sector built by the authors previously, which was based on real-life plants composition data of China's power sector in 2009, and could incorporate all possible actions of the power sector, including plants construction, decommission, and application of carbon capture and sequestration (CCS) on coal-fuelled plants, the implementation effects of three carbon mitigation policies were studied quantitatively, achieving a conclusion that the so-called “Surplus-Punishment & Deficit-Award” carbon tax policy is the best from the viewpoint of increasing CO2 reduction effect and also reducing the accumulated total cost. Based on this conclusion, the corresponding relationships between CO2 reduction objectives (including the accumulated total emissions reduction by the objective year and the annual emissions reduction in the objective year) were presented in detail. This work provides both directional and quantitative suggestions for China to make carbon mitigation policies in the future.

Suggested Citation

  • Zhang, Dongjie & Ma, Linwei & Liu, Pei & Zhang, Lili & Li, Zheng, 2012. "A multi-period superstructure optimisation model for the optimal planning of China's power sector considering carbon dioxide mitigation," Energy Policy, Elsevier, vol. 41(C), pages 173-183.
    • Handle: RePEc:eee:enepol:v:41:y:2012:i:c:p:173-183
    DOI: 10.1016/j.enpol.2011.10.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421511008159
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2011.10.031?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Lu, Chuanyi & Tong, Qing & Liu, Xuemei, 2010. "The impacts of carbon tax and complementary policies on Chinese economy," Energy Policy, Elsevier, vol. 38(11), pages 7278-7285, November.
    2. Zugang Liu & Trisha Woolley & Anna Nagurney, 2006. "Optimal Endogenous Carbon Taxes for Electric Power Supply Chains with Power Plants," Computing in Economics and Finance 2006 322, Society for Computational Economics.
    3. Shrestha, Ram M. & Marpaung, Charles O. P., 1999. "Supply- and demand-side effects of carbon tax in the Indonesian power sector: an integrated resource planning analysis," Energy Policy, Elsevier, vol. 27(4), pages 185-194, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Xiao, Jin & Li, Guohao & Xie, Ling & Wang, Shouyang & Yu, Lean, 2021. "Decarbonizing China's power sector by 2030 with consideration of technological progress and cross-regional power transmission," Energy Policy, Elsevier, vol. 150(C).
    2. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano & Irabien, Angel, 2012. "MINLP model for optimizing electricity production from coal-fired power plants considering carbon management," Energy Policy, Elsevier, vol. 51(C), pages 493-501.
    3. Li, Weiqi & Dai, Yaping & Ma, Linwei & Hao, Han & Lu, Haiyan & Albinson, Rosemary & Li, Zheng, 2015. "Oil-saving pathways until 2030 for road freight transportation in China based on a cost-optimization model," Energy, Elsevier, vol. 86(C), pages 369-384.
    4. 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).
    5. Yuan, Jiahai & Xu, Yan & Kang, Junjie & Zhang, Xingping & Hu, Zheng, 2014. "Nonlinear integrated resource strategic planning model and case study in China's power sector planning," Energy, Elsevier, vol. 67(C), pages 27-40.
    6. Almansoori, Ali & Betancourt-Torcat, Alberto, 2015. "Design optimization model for the integration of renewable and nuclear energy in the United Arab Emirates’ power system," Applied Energy, Elsevier, vol. 148(C), pages 234-251.
    7. Zhang, Xiaodong & Duncan, Ian J. & Huang, Gordon & Li, Gongchen, 2014. "Identification of management strategies for CO2 capture and sequestration under uncertainty through inexact modeling," Applied Energy, Elsevier, vol. 113(C), pages 310-317.
    8. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    9. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    10. 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.
    11. Wang, Can & Ye, Minhua & Cai, Wenjia & Chen, Jining, 2014. "The value of a clear, long-term climate policy agenda: A case study of China’s power sector using a multi-region optimization model," Applied Energy, Elsevier, vol. 125(C), pages 276-288.
    12. Maitri Verma & Alok Kumar Verma & A. K. Misra, 2021. "Mathematical modeling and optimal control of carbon dioxide emissions from energy sector," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13919-13944, September.
    13. Chen, Hao & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2016. "A multi-period power generation planning model incorporating the non-carbon external costs: A case study of China," Applied Energy, Elsevier, vol. 183(C), pages 1333-1345.
    14. Eto, R. & Murata, A. & Uchiyama, Y. & Okajima, K., 2013. "Co-benefits of including CCS projects in the CDM in India's power sector," Energy Policy, Elsevier, vol. 58(C), pages 260-268.
    15. Narimani, Mohammad Rasoul & Azizipanah-Abarghooee, Rasoul & Zoghdar-Moghadam-Shahrekohne, Behrouz & Gholami, Kayvan, 2013. "A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type," Energy, Elsevier, vol. 49(C), pages 119-136.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Assaad Ghazouani & Wanjun Xia & Mehdi Ben Jebli & Umer Shahzad, 2020. "Exploring the Role of Carbon Taxation Policies on CO 2 Emissions: Contextual Evidence from Tax Implementation and Non-Implementation European Countries," Sustainability, MDPI, vol. 12(20), pages 1-16, October.
    2. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    3. William Wills & Emilio Lebre La Rovere & Carolina Grottera & Giovanna Ferrazzo Naspolini & Gaëlle Le Treut & F. Ghersi & Julien Lefèvre & Carolina Burle Schmidt Dubeux, 2022. "Economic and social effectiveness of carbon pricing schemes to meet Brazilian NDC targets," Post-Print hal-03500923, HAL.
    4. Choi, Jun-Ki & Bakshi, Bhavik R. & Haab, Timothy, 2010. "Effects of a carbon price in the U.S. on economic sectors, resource use, and emissions: An input-output approach," Energy Policy, Elsevier, vol. 38(7), pages 3527-3536, July.
    5. Shree Shakya & S. Kumar & Ram Shrestha, 2012. "Co-benefits of a carbon tax in Nepal," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 17(1), pages 77-101, January.
    6. Tsao, Yu-Chung & Vu, Thuy-Linh, 2019. "Power supply chain network design problem for smart grid considering differential pricing and buy-back policies," Energy Economics, Elsevier, vol. 81(C), pages 493-502.
    7. Yakut, Aykut Mert & de Bruin, Kelly, 2023. "The importance of having a more realistic welfare transfer determination rule: A CGE analysis for Ireland," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1310-1325.
    8. Nusrate Aziz & Belayet Hossain & Laura Lamb, 2022. "Does green policy pay dividends?," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(2), pages 147-172, April.
    9. Yi, Qun & Gong, Min-Hui & Huang, Yi & Feng, Jie & Hao, Yan-Hong & Zhang, Ji-Long & Li, Wen-Ying, 2016. "Process development of coke oven gas to methanol integrated with CO2 recycle for satisfactory techno-economic performance," Energy, Elsevier, vol. 112(C), pages 618-628.
    10. Baratsas, Stefanos G. & Niziolek, Alexander M. & Onel, Onur & Matthews, Logan R. & Floudas, Christodoulos A. & Hallermann, Detlef R. & Sorescu, Sorin M. & Pistikopoulos, Efstratios N., 2022. "A novel quantitative forecasting framework in energy with applications in designing energy-intelligent tax policies," Applied Energy, Elsevier, vol. 305(C).
    11. Genovaitė Liobikienė & Mindaugas Butkus & Kristina Matuzevičiūtė, 2019. "The Contribution of Energy Taxes to Climate Change Policy in the European Union (EU)," Resources, MDPI, vol. 8(2), pages 1-23, April.
    12. Ren Yishuai & Jiang Yong & Ma Chaoqun & Liu Jianglong & Chen Jing, 2021. "Will Tax Burden Be a Stumbling Block to Carbon-Emission Reduction? Evidence from OECD Countries," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 335-355, August.
    13. Di Cosmo, Valeria & Hyland, Marie, 2013. "Carbon tax scenarios and their effects on the Irish energy sector," Energy Policy, Elsevier, vol. 59(C), pages 404-414.
    14. Sun, Yuanyuan & Mao, Xianqiang & Liu, Gengyuan & Yin, Xinan & Zhao, Yanwei, 2020. "Modelling the effects of energy taxes on ecological footprint transfers in China's foreign trade," Ecological Modelling, Elsevier, vol. 431(C).
    15. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    16. Zhang, Jinzhu & Liu, Yu & Zhou, Meifang & Chen, Boyang & Liu, Yawen & Cheng, Baodong & Xue, Jinjun & Zhang, Wei, 2022. "Regulatory effect of improving environmental information disclosure under environmental tax in China: From the perspectives of temporal and industrial heterogeneity," Energy Policy, Elsevier, vol. 164(C).
    17. Hafezalkotob, Ashkan, 2017. "Competition, cooperation, and coopetition of green supply chains under regulations on energy saving levels," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 228-250.
    18. Chaabane, A. & Ramudhin, A. & Paquet, M., 2012. "Design of sustainable supply chains under the emission trading scheme," International Journal of Production Economics, Elsevier, vol. 135(1), pages 37-49.
    19. Shu Mo & Ting Wang, 2022. "Synergistic Effects of International Oil Price Fluctuations and Carbon Tax Policies on the Energy–Economy–Environment System in China," IJERPH, MDPI, vol. 19(21), pages 1-17, October.
    20. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).

    Corrections

    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:enepol:v:41:y:2012:i:c:p:173-183. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.