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Multi-stage stochastic planning for a long-term low-carbon transition of island power system considering carbon price uncertainty and offshore wind power

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  • Wang, Bangyan
  • Wang, Xiuli
  • Wei, Fengting
  • Shao, Chengcheng
  • Zhou, Jiahao
  • Lin, Jintian

Abstract

The characteristics of isolated grids lead island power systems to rely on stable conventional generation, which is not environmentally friendly and has high carbon emissions. This paper proposes a low-carbon transition model for island power systems considering large-scale offshore wind resources and the long-term uncertainty of carbon prices. First, a detailed model for offshore wind power systems is proposed considering the interaction of multiple wind farms and three transmission technologies. Second, a multi-stage power system planning model is established including the upgrading and decommissioning of thermal units. Meanwhile, an improved long-term carbon price uncertainty modeling method based on the binomial tree is proposed. Then, focusing on the uncertainty of carbon prices, a multi-stage stochastic optimization model is established, and the stochastic nested decomposition algorithm is used to solve the problem. Finally, numerical results show that the low-carbon transition develops plenty of offshore wind power as the primary power source and usually adopts a fractional frequency transmission system for offshore wind integration. The uncertainty of carbon prices has a significant impact on the transition: in the high carbon price realization, the annual carbon emissions are only 0.088 Mt, while in the low carbon price realization, the annual emissions are 0.255 Mt.

Suggested Citation

  • Wang, Bangyan & Wang, Xiuli & Wei, Fengting & Shao, Chengcheng & Zhou, Jiahao & Lin, Jintian, 2023. "Multi-stage stochastic planning for a long-term low-carbon transition of island power system considering carbon price uncertainty and offshore wind power," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223017437
    DOI: 10.1016/j.energy.2023.128349
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