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Research on integrated resource strategic planning based on complex uncertainty simulation with case study of China

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  • Zheng, Yanan
  • Ren, Dongming
  • Guo, Zheyu
  • Hu, Zhaoguang
  • Wen, Quan

Abstract

In response to climate change, developing renewable energy has become a main way of energy transition in many countries. In terms of medium-and long-term, the development of renewable energy generation technologies, such as wind and solar, is certain to face uncertainties. More than this, power demand and other factors are also facing many complex uncertainties. However, traditional planning methods are not able to take various uncertainties into account. In the past, the serious underestimation of uncertainties existing in the development caused China’s a series of problems, such as renewables curtailment. Therefore, this paper firstly reviews the current status and the existing problems of renewable energy generation in China, and discusses the crucial uncertainty factors affecting medium-and long-term renewable energy planning; and then, the complex uncertainty models of power demand and renewable energy generation cost are built respectively, and the improved integrated resource strategic planning model is proposed; finally, by using the proposed model China’s wind, solar and biomass power development during 2016–2030 is studied from the perspective of big data planning, and the advantages and drawbacks of the improved method is discussed.

Suggested Citation

  • Zheng, Yanan & Ren, Dongming & Guo, Zheyu & Hu, Zhaoguang & Wen, Quan, 2019. "Research on integrated resource strategic planning based on complex uncertainty simulation with case study of China," Energy, Elsevier, vol. 180(C), pages 772-786.
    • Handle: RePEc:eee:energy:v:180:y:2019:i:c:p:772-786
    DOI: 10.1016/j.energy.2019.05.120
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    References listed on IDEAS

    as
    1. Sarica, Kemal & Tyner, Wallace E., 2013. "Analysis of US renewable fuels policies using a modified MARKAL model," Renewable Energy, Elsevier, vol. 50(C), pages 701-709.
    2. Vithayasrichareon, Peerapat & MacGill, Iain F., 2012. "Portfolio assessments for future generation investment in newly industrializing countries – A case study of Thailand," Energy, Elsevier, vol. 44(1), pages 1044-1058.
    3. Zheng, Yanan & Hu, Zhaoguang & Wang, Jianhui & Wen, Quan, 2014. "IRSP (integrated resource strategic planning) with interconnected smart grids in integrating renewable energy and implementing DSM (demand side management) in China," Energy, Elsevier, vol. 76(C), pages 863-874.
    4. Doucette, Reed T. & McCulloch, Malcolm D., 2011. "Modeling the CO2 emissions from battery electric vehicles given the power generation mixes of different countries," Energy Policy, Elsevier, vol. 39(2), pages 803-811, February.
    5. Jean Château & Bertrand Magné & Laura Cozzi, 2014. "Economic Implications of the IEA Efficient World Scenario," OECD Environment Working Papers 64, OECD Publishing.
    6. Vithayasrichareon, Peerapat & MacGill, Iain F., 2012. "A Monte Carlo based decision-support tool for assessing generation portfolios in future carbon constrained electricity industries," Energy Policy, Elsevier, vol. 41(C), pages 374-392.
    7. Alban Kitous, Patrick Criqui, Elie Bellevrat and Bertrand Chateau, 2010. "Transformation Patterns of the Worldwide Energy System - Scenarios for the Century with the POLES Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    8. Hu, Zhaoguang & Tan, Xiandong & Yang, Fan & Yang, Ming & Wen, Quan & Shan, Baoguo & Han, Xinyang, 2010. "Integrated resource strategic planning: Case study of energy efficiency in the Chinese power sector," Energy Policy, Elsevier, vol. 38(11), pages 6391-6397, November.
    9. McPherson, Madeleine & Karney, Bryan, 2014. "Long-term scenario alternatives and their implications: LEAP model application of Panama׳s electricity sector," Energy Policy, Elsevier, vol. 68(C), pages 146-157.
    10. Ghelichi, Zabih & Saidi-Mehrabad, Mohammad & Pishvaee, Mir Saman, 2018. "A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: A case study," Energy, Elsevier, vol. 156(C), pages 661-687.
    11. Cai, Mengting & Huang, Guohe & Chen, Jiapei & Li, Yunhuan & Fan, Yurui, 2018. "A generalized fuzzy chance-constrained energy systems planning model for Guangzhou, China," Energy, Elsevier, vol. 165(PA), pages 191-204.
    12. Spiecker, Stephan & Weber, Christoph, 2014. "The future of the European electricity system and the impact of fluctuating renewable energy – A scenario analysis," Energy Policy, Elsevier, vol. 65(C), pages 185-197.
    Full references (including those not matched with items on IDEAS)

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    1. Zhu, Yanlei & Song, Yan & Yuan, Jiahai, 2021. "Structural distortion and the shortage of peak-load power resources in China: A screening curve approach and case study of Shandong Province," Utilities Policy, Elsevier, vol. 70(C).

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