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A multi-regional modelling and optimization approach to China's power generation and transmission planning

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  • Guo, Zheng
  • Ma, Linwei
  • Liu, Pei
  • Jones, Ian
  • Li, Zheng

Abstract

Power demand in China has increased rapidly in the past decade, and it is projected to grow even further. To gain insights into how this demand growth could optimally be met, addressing regional differences such as resource distribution and power demand, is crucial. For long-term planning purposes, using a multi-regional mathematical model that divides China's power sector into regions overcomes the limitations of viewing as a single network. Reflecting how inter-regional power transmission could best be utilized is critical in understanding how flows between regions could be optimised. In this paper, a multi-regional model that reflects actual grid infrastructure with an objective function to maximize accumulated total profits gained by the power generation sector from 2013 to 2050 is proposed. A case study is provided to illustrate how inter-regional power transmission could influence the regional deployment of technologies under different policy scenarios. The results show that energy subsidies and national targets will remain important to the deployment of renewable energy in both the short and long term. In addition, potential downside implications of lower demand growth on the long-term prospects of long-distance inter-regional power transmission and options, such as more flexible electricity pricing mechanisms, to limit the effects are discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:116:y:2016:i:p2:p:1348-1359
    DOI: 10.1016/j.energy.2016.06.035
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    References listed on IDEAS

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    1. Zheng Guo & Pei Liu & Linwei Ma & Zheng Li, 2015. "Effects of Low-Carbon Technologies and End-Use Electrification on Energy-Related Greenhouse Gases Mitigation in China by 2050," Energies, MDPI, vol. 8(7), pages 1-24, July.
    2. Mischke, Peggy & Karlsson, Kenneth B., 2014. "Modelling tools to evaluate China's future energy system – A review of the Chinese perspective," Energy, Elsevier, vol. 69(C), pages 132-143.
    3. 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.
    4. 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.
    5. 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.
    6. Huber, Matthias & Weissbart, Christoph, 2015. "On the optimal mix of wind and solar generation in the future Chinese power system," Energy, Elsevier, vol. 90(P1), pages 235-243.
    7. Zhou, Xiaoxin & Yi, Jun & Song, Ruihua & Yang, Xiaoyu & Li, Yan & Tang, Haiyan, 2010. "An overview of power transmission systems in China," Energy, Elsevier, vol. 35(11), pages 4302-4312.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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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