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Optimal dispatching of large-scale electric vehicles into grid based on improved second-order cone

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  • Yin, WanJun
  • Qin, Xuan
  • Huang, ZhiZhong

Abstract

The disordered charging behavior of large-scale electric vehicles will have an immeasurable impact on the distribution grid. How to simultaneously solve the demand for charging and discharging of large-scale electric vehicles and the safe operation of the distribution grid has been a research hotspot in recent years. In response to this problem, firstly, we mathematically model the problem; secondly, according to the nonlinear characteristics of the optimization model, in order to find the optimal solution accurately and quickly, using the improved second-order cone method to transform it, which solves the problem well:(1) “Where” problem, that is, to find the best nodes to charge and discharge electric vehicles in the distribution grid, (2) “When” problem, that is, when is the best time to charge and discharge electric vehicles, (3) “How” problem, that is, how many electric vehicles are connected to the distribution grid at the right location and the right time. Finally, using the Matlab-based Yalmip modeling tool to call the Cplex mathematical solver to verify the IEEE-33 nodes power distribution system, the results show that the proposed method not only solves the charging and discharging requirements of large-scale electric vehicles, but also ensures the stability of the power grid run.

Suggested Citation

  • Yin, WanJun & Qin, Xuan & Huang, ZhiZhong, 2022. "Optimal dispatching of large-scale electric vehicles into grid based on improved second-order cone," Energy, Elsevier, vol. 254(PB).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s036054422201249x
    DOI: 10.1016/j.energy.2022.124346
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    References listed on IDEAS

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    1. Tabatabaee, Sajad & Mortazavi, Seyed Saeedallah & Niknam, Taher, 2017. "Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources," Energy, Elsevier, vol. 121(C), pages 480-490.
    2. Yin, WanJun & Ming, ZhengFeng & Wen, Tao, 2021. "Scheduling strategy of electric vehicle charging considering different requirements of grid and users," Energy, Elsevier, vol. 232(C).
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    Cited by:

    1. Yin, Wanjun & Ji, Jianbo & Wen, Tao & Zhang, Chao, 2023. "Study on orderly charging strategy of EV with load forecasting," Energy, Elsevier, vol. 278(C).
    2. Yin, Wanjun & Ji, Jianbo & Qin, Xuan, 2023. "Study on optimal configuration of EV charging stations based on second-order cone," Energy, Elsevier, vol. 284(C).
    3. Aissa Benhammou & Mohammed Amine Hartani & Hamza Tedjini & Hegazy Rezk & Mujahed Al-Dhaifallah, 2023. "Improvement of Autonomy, Efficiency, and Stress of Fuel Cell Hybrid Electric Vehicle System Using Robust Controller," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    4. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).

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