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Energy optimal scheduling strategy considering V2G characteristics of electric vehicle

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  • Yin, Wanjun
  • Jia, Leilei
  • Ji, Jianbo

Abstract

in recent years, large-scale electric vehicles connected to the power grid has a significant impact on demand-side resources. In addition, the vehicle-to-grid technology of electric vehicles introduces more uncertainties, which brings great challenges to the optimal scheduling of integrated energy systems. To solve this problem, this paper fully considers the uncertainty and fluctuation of wind power. Firstly, the objective function of joint configuration is constructed to maximize the utilization of wind power and minimize the planned generation cost of the system. Secondly, the linearized power flow equations are used to represent the relations among the state variables, and the second-order cone relaxation method is applied to deal with the branch power flow constraints, which is transformed into a solvable mixed-integer second-order cone programming model. Finally, the validity of the model is verified by an example. The system achieves obvious peak-shaving and valley-filling effect and improves the economic benefit of the system.

Suggested Citation

  • Yin, Wanjun & Jia, Leilei & Ji, Jianbo, 2024. "Energy optimal scheduling strategy considering V2G characteristics of electric vehicle," Energy, Elsevier, vol. 294(C).
    • Handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224007394
    DOI: 10.1016/j.energy.2024.130967
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    References listed on IDEAS

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    1. Yongxing Wang & Jun Bi & Chaoru Lu & Cong Ding, 2020. "Route Guidance Strategies for Electric Vehicles by Considering Stochastic Charging Demands in a Time-Varying Road Network," Energies, MDPI, vol. 13(9), pages 1-24, May.
    2. Yang, Jun & He, Lifu & Fu, Siyao, 2014. "An improved PSO-based charging strategy of electric vehicles in electrical distribution grid," Applied Energy, Elsevier, vol. 128(C), pages 82-92.
    3. Wu, Ji & Su, Hao & Meng, Jinhao & Lin, Mingqiang, 2023. "Electric vehicle charging scheduling considering infrastructure constraints," Energy, Elsevier, vol. 278(PA).
    4. Erdogan, Nuh & Kucuksari, Sadik & Murphy, Jimmy, 2022. "A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies," Energy, Elsevier, vol. 254(PA).
    5. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
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    1. Zhao, Xudong & Wang, Yibo & Liu, Chuang & Cai, Guowei & Ge, Weichun & Wang, Bowen & Wang, Dongzhe & Shang, Jingru & Zhao, Yiru, 2024. "Two-stage day-ahead and intra-day scheduling considering electric arc furnace control and wind power modal decomposition," Energy, Elsevier, vol. 302(C).

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    More about this item

    Keywords

    EV; V2G; Energy; Optimization; Scheduling;
    All these keywords.

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