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Hyperfine optimal dispatch for integrated energy microgrid considering uncertainty

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  • Bo, Yaolong
  • Xia, Yanghong
  • Wei, Wei
  • Li, Zichen
  • Zhao, Bo
  • Lv, Zeyan

Abstract

Different from the traditional microgrid, the optimal dispatch of integrated energy microgrid (IEM) may face the problems of infeasibility, non-convexity and quantification of uncertainties. To fill this gap, this paper presents the hyperfine optimal dispatch methodology for IEM considering uncertainties. The proposed method not only reveals the impact of time resolution for integrated energy optimal dispatch, but also solves the uncertainty of photovoltaic (PV) power prediction error based on distributionally robust optimization (DRO). To cape with the complexity and non-convexity of the proposed model, a piecewise McCormick algorithm with parallel computation is constructed. The case studies are performed to demonstrate the benefits of the proposed optimal dispatch in terms of operation economics, model feasibility, optimization computation time and robustness.

Suggested Citation

  • Bo, Yaolong & Xia, Yanghong & Wei, Wei & Li, Zichen & Zhao, Bo & Lv, Zeyan, 2023. "Hyperfine optimal dispatch for integrated energy microgrid considering uncertainty," Applied Energy, Elsevier, vol. 334(C).
    • Handle: RePEc:eee:appene:v:334:y:2023:i:c:s0306261923000016
    DOI: 10.1016/j.apenergy.2023.120637
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    Cited by:

    1. Li, Zichen & Xia, Yanghong & Bo, Yaolong & Wei, Wei, 2024. "Optimal planning for electricity-hydrogen integrated energy system considering multiple timescale operations and representative time-period selection," Applied Energy, Elsevier, vol. 362(C).
    2. Liu, Fan & Duan, Jiandong & Wu, Chen & Tian, Qinxing, 2024. "Risk-averse distributed optimization for integrated electricity-gas systems considering uncertainties of Wind-PV and power-to-gas," Renewable Energy, Elsevier, vol. 227(C).
    3. Liu, Zhi-Feng & Zhao, Shi-Xiang & Zhang, Xi-Jia & Tang, Yu & You, Guo-Dong & Li, Ji-Xiang & Zhao, Shuang-Le & Hou, Xiao-Xin, 2023. "Renewable energy utilizing and fluctuation stabilizing using optimal dynamic grid connection factor strategy and artificial intelligence-based solution method," Renewable Energy, Elsevier, vol. 219(P1).

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