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Two-stage real-time optimal electricity dispatch strategy for urban residential quarter with electric vehicles’ charging load

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  • Li, Yipu
  • Su, Hao
  • Zhou, Yun
  • Chen, Lixia
  • Shi, Yiwei
  • Li, Hengjie
  • Feng, Donghan

Abstract

The potential of demand-side management and the schedulable ability of electric vehicles (EVs) encourage demand-side management operators such as residential load aggregators to dispatch the electricity demand and supply of the residential quarter and enhance the economics and security of energy use. Considering the uncertainties in the arrival time, departure time, and charging amount of EVs, a two-stage real-time optimal electricity dispatch strategy for residential quarters with EVs' charging load is proposed here. First, a real-time optimal approach is proposed based on the receding horizon optimization process to decompose the day-ahead optimal period into sequential advanced optimization horizons. Second, considering the dual optimization goals of economics and security, a two-stage optimization procedure is proposed for the residential quarter's electricity dispatch in the advanced optimization horizon. Specifically, the first-stage optimization model aims to minimize the total cost of electricity of the residential quarter. And the second-stage optimization model is to minimize the peak-valley load difference of the residential quarter. Based on these models, a solving timeline with detailed steps for the proposed two-stage real-time optimal electricity dispatch strategy is presented. Finally, case studies on the data of a real residential quarter located in Shanghai demonstrate the effectiveness of the proposed methodology.

Suggested Citation

  • Li, Yipu & Su, Hao & Zhou, Yun & Chen, Lixia & Shi, Yiwei & Li, Hengjie & Feng, Donghan, 2023. "Two-stage real-time optimal electricity dispatch strategy for urban residential quarter with electric vehicles’ charging load," Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000968
    DOI: 10.1016/j.energy.2023.126702
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    References listed on IDEAS

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    Cited by:

    1. Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
    2. Jiang, Hou & Yao, Ling & Lu, Ning & Qin, Jun & Zhang, Xiaotong & Liu, Tang & Zhang, Xingxing & Zhou, Chenghu, 2024. "Exploring the optimization of rooftop photovoltaic scale and spatial layout under curtailment constraints," Energy, Elsevier, vol. 293(C).
    3. Heping Jia & Qianxin Ma & Yun Li & Mingguang Liu & Dunnan Liu, 2023. "Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation," Energies, MDPI, vol. 16(17), pages 1-18, August.
    4. Zhang, Rui & Yu, Jilai, 2024. "Evaluating multi-dimensional response capability of electric bus considering carbon emissions and traffic index," Energy, Elsevier, vol. 286(C).

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