IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v185y2017ip1p556-572.html
   My bibliography  Save this article

A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector

Author

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

Abstract

Future development of China’s electricity system will not only need to consider generation capacity needed to meet demand but also economic and flexible technologies to meet peak demand and integrate increasing volumes of intermittent renewable generation. This paper describes research in which a multi-region dispatch model was established and analysis performed to gain insights into optimal choices for the development of China’s electricity sector. The model reflected China’s regional electricity demand profiles, its natural resource distribution, its inter-regional electricity transmission network, performance characteristics of different electricity generating technologies, and temporal electricity demand variations. The case study included a cap-and-trade carbon mitigation scheme to enable direct comparison with previous studies that lacked the temporal element considerations. The results highlighted the importance of considering even short-term temporal variations when planning the long-term development of electricity systems. They also demonstrated how Natural Gas Combined Cycle turbines (NGCC) are well suited to providing peak-demand regulation capability. Whilst, the analysis indicates that coal-fired plants are set to continue to play a significant role through out to 2050. The modelling also confirms the deployment of renewable energy in the long-term future and as a result the requirement of flexible generation to maintain stability and integrity.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p1:p:556-572
    DOI: 10.1016/j.apenergy.2016.10.132
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916315823
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.10.132?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. Viebahn, Peter & Vallentin, Daniel & Höller, Samuel, 2015. "Prospects of carbon capture and storage (CCS) in China’s power sector – An integrated assessment," Applied Energy, Elsevier, vol. 157(C), pages 229-244.
    2. 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.
    3. 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.
    4. 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.
    5. Huber, Matthias & Roger, Albert & Hamacher, Thomas, 2015. "Optimizing long-term investments for a sustainable development of the ASEAN power system," Energy, Elsevier, vol. 88(C), pages 180-193.
    6. 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.
    7. 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.
    8. Wang, Hao & Nakata, Toshihiko, 2009. "Analysis of the market penetration of clean coal technologies and its impacts in China's electricity sector," Energy Policy, Elsevier, vol. 37(1), pages 338-351, January.
    9. Gnansounou, Edgard & Dong, Jun, 2004. "Opportunity for inter-regional integration of electricity markets: the case of Shandong and Shanghai in East China," Energy Policy, Elsevier, vol. 32(15), pages 1737-1751, October.
    10. 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.
    11. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2016. "Optimization modeling to support renewables integration in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 316-325.
    12. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    13. 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.
    14. Denholm, Paul & Hand, Maureen, 2011. "Grid flexibility and storage required to achieve very high penetration of variable renewable electricity," Energy Policy, Elsevier, vol. 39(3), pages 1817-1830, March.
    15. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    16. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    17. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2016. "An optimization framework for the integrated planning of generation and transmission expansion in interconnected power systems," Applied Energy, Elsevier, vol. 170(C), pages 1-21.
    18. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    19. Wang, Ke & Wang, Can & Lu, Xuedu & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's iron and steel industry," Energy Policy, Elsevier, vol. 35(4), pages 2320-2335, April.
    20. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
    21. 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.
    22. 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)

    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 & 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.
    2. 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.
    3. Peng Wang & Meng Li, 2019. "Scenario Analysis in the Electric Power Industry under the Implementation of the Electricity Market Reform and a Carbon Policy in China," Energies, MDPI, vol. 12(11), pages 1-26, June.
    4. 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.
    5. 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.
    6. Tang, Bao-Jun & Li, Ru & Li, Xiao-Yi & Chen, Hao, 2017. "An optimal production planning model of coal-fired power industry in China: Considering the process of closing down inefficient units and developing CCS technologies," Applied Energy, Elsevier, vol. 206(C), pages 519-530.
    7. 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.
    8. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    9. Wang, Hongye & Su, Bin & Mu, Hailin & Li, Nan & Jiang, Bo & Kong, Xue, 2019. "Optimization of electricity generation and interprovincial trading strategies in Southern China," Energy, Elsevier, vol. 174(C), pages 696-707.
    10. Khanna, Nina Zheng & Zhou, Nan & Fridley, David & Ke, Jing, 2016. "Quantifying the potential impacts of China's power-sector policies on coal input and CO2 emissions through 2050: A bottom-up perspective," Utilities Policy, Elsevier, vol. 41(C), pages 128-138.
    11. 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).
    12. 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.
    13. Xiaopeng Guo & Xiaodan Guo & Jiahai Yuan, 2014. "Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China," Sustainability, MDPI, vol. 7(1), pages 1-21, December.
    14. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    15. Wang, Junfeng & He, Shutong & Qiu, Ye & Liu, Nan & Li, Yongjian & Dong, Zhanfeng, 2018. "Investigating driving forces of aggregate carbon intensity of electricity generation in China," Energy Policy, Elsevier, vol. 113(C), pages 249-257.
    16. Mertens, Tim & Poncelet, Kris & Duerinck, Jan & Delarue, Erik, 2020. "Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope," Applied Energy, Elsevier, vol. 261(C).
    17. Radhanon Diewvilai & Kulyos Audomvongseree, 2021. "Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints," Energies, MDPI, vol. 14(18), pages 1-25, September.
    18. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    19. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2016. "An optimization framework for the integrated planning of generation and transmission expansion in interconnected power systems," Applied Energy, Elsevier, vol. 170(C), pages 1-21.
    20. Liang, Yuanyuan & Yu, Biying & Wang, Lu, 2019. "Costs and benefits of renewable energy development in China's power industry," Renewable Energy, Elsevier, vol. 131(C), pages 700-712.

    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:185:y:2017:i:p1:p:556-572. 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.