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

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  • 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.

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  • 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
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    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.
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    23. Du, Binglin & Liu, Pei & Li, Zheng, 2023. "Coal power plants transition based on joint planning of power and central heating sectors: A case study of China," Energy, Elsevier, vol. 283(C).
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