IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v137y2015icp413-426.html
   My bibliography  Save this article

A multi-region optimization planning model for China’s power sector

Author

Listed:
  • Cheng, Rui
  • Xu, Zhaofeng
  • Liu, Pei
  • Wang, Zhe
  • Li, Zheng
  • Jones, Ian

Abstract

Demand for electricity in China kept accelerating in recent years; moreover, there exist serious mismatches among the distribution of power demand, energy resources, and power generation infrastructure across different regions in China, both of which indicate a necessity of a holistic and integrated approach to the strategic planning and development of its power industry. Material benefits could be realized by ensuring that the long term development of the power system is optimized by taking into consideration the different regional dynamics and characteristics. This paper proposes a multi-region optimization model that can deliver insights into how planning of the long term development of China’s power sector could minimize the total cost of China’s power sector by considering regional variations in availabilities of resources and inter-region power transmission line capacity. A case study considered how investment decisions to expand and alter the existing generation mix could be optimized across a timeframe from 2011 to 2050. By comparing results between single and multi-region optimizations, it was possible to show the likely impact on how investment decisions would differ when regional differences were taken into account. The multi-region optimization arguably better reflects and considers conditions and challenges in the real world.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:137:y:2015:i:c:p:413-426
    DOI: 10.1016/j.apenergy.2014.10.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914010642
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2014.10.023?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. Zhou, Wenji & Zhu, Bing & Fuss, Sabine & Szolgayová, Jana & Obersteiner, Michael & Fei, Weiyang, 2010. "Uncertainty modeling of CCS investment strategy in China's power sector," Applied Energy, Elsevier, vol. 87(7), pages 2392-2400, July.
    2. 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.
    3. Duan, Hong-Bo & Fan, Ying & Zhu, Lei, 2013. "What’s the most cost-effective policy of CO2 targeted reduction: An application of aggregated economic technological model with CCS?," Applied Energy, Elsevier, vol. 112(C), pages 866-875.
    4. Liu, Liwei & Zong, Haijing & Zhao, Erdong & Chen, Chuxiang & Wang, Jianzhou, 2014. "Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development," Applied Energy, Elsevier, vol. 124(C), pages 199-212.
    5. Zhu, Lei & Fan, Ying, 2011. "A real options–based CCS investment evaluation model: Case study of China’s power generation sector," Applied Energy, Elsevier, vol. 88(12), pages 4320-4333.
    6. Cai, Wenjia & Wang, Can & Wang, Ke & Zhang, Ying & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's electricity sector," Energy Policy, Elsevier, vol. 35(12), pages 6445-6456, December.
    7. 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.
    8. Zhang, Jianyun & Liu, Pei & Zhou, Zhe & Ma, Linwei & Li, Zheng & Ni, Weidou, 2014. "A mixed-integer nonlinear programming approach to the optimal design of heat network in a polygeneration energy system," Applied Energy, Elsevier, vol. 114(C), pages 146-154.
    9. Liu, Pei & Pistikopoulos, Efstratios N. & Li, Zheng, 2010. "An energy systems engineering approach to the optimal design of energy systems in commercial buildings," Energy Policy, Elsevier, vol. 38(8), pages 4224-4231, August.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    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. Guo, Zheng & Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian & Sun, Yong, 2017. "A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector," Applied Energy, Elsevier, vol. 185(P1), pages 556-572.
    2. Li, Ying & Lukszo, Zofia & Weijnen, Margot, 2015. "The implications of CO2 price for China’s power sector decarbonization," Applied Energy, Elsevier, vol. 146(C), pages 53-64.
    3. 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.
    4. Zhu, Lei & Fan, Ying, 2013. "Modelling the investment in carbon capture retrofits of pulverized coal-fired plants," Energy, Elsevier, vol. 57(C), pages 66-75.
    5. Fan, Jing-Li & Xu, Mao & Li, Fengyu & Yang, Lin & Zhang, Xian, 2018. "Carbon capture and storage (CCS) retrofit potential of coal-fired power plants in China: The technology lock-in and cost optimization perspective," Applied Energy, Elsevier, vol. 229(C), pages 326-334.
    6. Njomza Ibrahimi & Alemayehu Gebremedhin & Alketa Sahiti, 2019. "Achieving a Flexible and Sustainable Energy System: The Case of Kosovo," Energies, MDPI, vol. 12(24), pages 1-22, December.
    7. Yi, Bo-Wen & Xu, Jin-Hua & Fan, Ying, 2016. "Inter-regional power grid planning up to 2030 in China considering renewable energy development and regional pollutant control: A multi-region bottom-up optimization model," Applied Energy, Elsevier, vol. 184(C), pages 641-658.
    8. Zhang, Xian & Wang, Xingwei & Chen, Jiajun & Xie, Xi & Wang, Ke & Wei, Yiming, 2014. "A novel modeling based real option approach for CCS investment evaluation under multiple uncertainties," Applied Energy, Elsevier, vol. 113(C), pages 1059-1067.
    9. Zhang, Shuwei & Bauer, Nico & Luderer, Gunnar & Kriegler, Elmar, 2014. "Role of technologies in energy-related CO2 mitigation in China within a climate-protection world: A scenarios analysis using REMIND," Applied Energy, Elsevier, vol. 115(C), pages 445-455.
    10. Fan, Jing-Li & Xu, Mao & Yang, Lin & Zhang, Xian & Li, Fengyu, 2019. "How can carbon capture utilization and storage be incentivized in China? A perspective based on the 45Q tax credit provisions," Energy Policy, Elsevier, vol. 132(C), pages 1229-1240.
    11. Mo, Jian-Lei & Schleich, Joachim & Zhu, Lei & Fan, Ying, 2015. "Delaying the introduction of emissions trading systems—Implications for power plant investment and operation from a multi-stage decision model," Energy Economics, Elsevier, vol. 52(PB), pages 255-264.
    12. Lee, Suh-Young & Lee, Jae-Uk & Lee, In-Beum & Han, Jeehoon, 2017. "Design under uncertainty of carbon capture and storage infrastructure considering cost, environmental impact, and preference on risk," Applied Energy, Elsevier, vol. 189(C), pages 725-738.
    13. Zhang, Minkai & Guo, Yincheng, 2013. "Rate based modeling of absorption and regeneration for CO2 capture by aqueous ammonia solution," Applied Energy, Elsevier, vol. 111(C), pages 142-152.
    14. Rochedo, Pedro R.R. & Szklo, Alexandre, 2013. "Designing learning curves for carbon capture based on chemical absorption according to the minimum work of separation," Applied Energy, Elsevier, vol. 108(C), pages 383-391.
    15. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.
    16. Zhang, M.M. & Wang, Qunwei & Zhou, Dequn & Ding, H., 2019. "Evaluating uncertain investment decisions in low-carbon transition toward renewable energy," Applied Energy, Elsevier, vol. 240(C), pages 1049-1060.
    17. Herui Cui & Tian Zhao & Ruirui Wu, 2018. "An Investment Feasibility Analysis of CCS Retrofit Based on a Two-Stage Compound Real Options Model," Energies, MDPI, vol. 11(7), pages 1-19, July.
    18. Li, Tianxiao & Li, Zheng & Li, Weiqi, 2020. "Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model," Renewable Energy, Elsevier, vol. 156(C), pages 851-863.
    19. Carmen Schiel & Simon Glöser-Chahoud & Frank Schultmann, 2019. "A real option application for emission control measures," Journal of Business Economics, Springer, vol. 89(3), pages 291-325, April.
    20. Zhang, M.M. & Zhou, D.Q. & Zhou, P. & Chen, H.T., 2017. "Optimal design of subsidy to stimulate renewable energy investments: The case of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 873-883.

    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:appene:v:137:y:2015:i:c:p:413-426. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.