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A multi-stage planning model for low-carbon power systems: Coupling oxy-fuel carbon capture retrofitting with power-to-methanol

  • School of Electrical Engineering
  • State Grid Corporation of China

Research output: Contribution to journal › Article › peer-review

Abstract

The low-carbon transition of power systems requires a realistic transition pathway for large fleets of existing coal-fired units, yet retrofit pathways based on oxy-fuel combustion with carbon capture remain largely overlooked in planning studies. This paper proposes a multi-stage planning model in which the retrofitting of traditional thermal power plants into oxy-fuel carbon capture plants is coordinated with the deployment of power-to-methanol stations. A bidirectional mass–energy loop is established through an oxygen feedback mechanism: the oxygen byproduct of electrolysis is recovered to mitigate the air-separation energy penalty, while the captured carbon dioxide is converted into value-added methanol. To address the long-term uncertainties in the carbon price and the renewable penetration, the transition is formulated as a multi-stage stochastic program, in which the investment decisions adapt sequentially as uncertainty is resolved. To tackle the resulting computational complexity, an enhanced stochastic dual dynamic integer programming algorithm is developed, in which an adaptive precision strategy accelerates convergence and a verification mechanism eliminates the risk of false optimality. Case studies on two test systems validate the effectiveness of the proposed method, and show that the synergy between the retrofitted plants and the methanol stations provides an economically sustainable route for the deep decarbonization of existing coal-fired assets.

Original languageEnglish
Article number142452
JournalEnergy
Volume364
DOIs
StatePublished - 1 Nov 2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Low-carbon transition
  • Multi-stage stochastic programming
  • Oxy-fuel combustion
  • Power-to-methanol
  • Unit retrofitting

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