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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

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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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