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Big data twin recombination networks for grid low-carbon economic dispatch decision optimization

Author

Listed:
  • Chang Liu
  • Jianfeng Wu
  • Yu Chen
  • Jianguo Wang
  • Tao Wang
  • Kairui Hu
  • Jianchao Wu

Abstract

To improve the low-carbon economic dispatch, we introduced a big data twin recombination network for grid low-carbon economic dispatch decision optimization. we quantified the energy structure and corrected the linear regression of power loads to boost grid dispatch efficiency, and optimized the correlation between the scheduling of power generation facilities and economic operational strategies by mapping and decomposing, expediting the cyclic relevance of the dispatch decision model. Results demonstrated that our method can optimize decision-making for grid economic dispatch and establish reliable correlation analysis models concerning carbon emissions, grid operational costs, energy utilization efficiency, and power load matching precision.

Suggested Citation

  • Chang Liu & Jianfeng Wu & Yu Chen & Jianguo Wang & Tao Wang & Kairui Hu & Jianchao Wu, 2025. "Big data twin recombination networks for grid low-carbon economic dispatch decision optimization," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 384-393.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:384-393.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf014
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