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Cooperative optimization strategy for large-scale electric vehicle charging and discharging

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  • Yin, WanJun
  • Qin, Xuan

Abstract

In order to match the basic load of the power grid and the charging demand of electric vehicles, this paper fully considers the high pollution and non-renewability of coal-fired power generation, the clean and renewable nature of wind power, and the characteristics of intermittent and fluctuation. In this paper, a high-confidence wind power scenario is used to establish a multi-objective optimal scheduling model that considers the V2G characteristics of electric vehicles, generator operating costs, abandoned air volume, environmental pollution, and charging costs for electric vehicle users, the optimal multi-objective scheduling model adopts CPLEX solver tool, by setting the simulation comparison of three scenarios: non-electric vehicle charging, electric vehicle charging, and electric vehicle charging and discharging, the calculation results show that the proposed optimal scheduling strategy realizes the collaborative optimization of thermal power units, wind power and electric vehicles. This paper provides a solution for the optimal scheduling of large-scale electric vehicles connected to the grid.

Suggested Citation

  • Yin, WanJun & Qin, Xuan, 2022. "Cooperative optimization strategy for large-scale electric vehicle charging and discharging," Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:energy:v:258:y:2022:i:c:s0360544222018680
    DOI: 10.1016/j.energy.2022.124969
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    References listed on IDEAS

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    1. Yang, Chao & Liu, Kaijia & Jiao, Xiaohong & Wang, Weida & Chen, Ruihu & You, Sixiong, 2022. "An adaptive firework algorithm optimization-based intelligent energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 239(PB).
    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. Khokhar, Bhuvnesh & Parmar, K. P. Singh, 2022. "A novel adaptive intelligent MPC scheme for frequency stabilization of a microgrid considering SoC control of EVs," Applied Energy, Elsevier, vol. 309(C).
    4. Wang, Jianzhou & Song, Yiliao & Liu, Feng & Hou, Ru, 2016. "Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 960-981.
    5. Dini, Anoosh & Hassankashi, Alireza & Pirouzi, Sasan & Lehtonen, Matti & Arandian, Behdad & Baziar, Ali Asghar, 2022. "A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response," Energy, Elsevier, vol. 239(PA).
    6. Andersson, Öivind & Börjesson, Pål, 2021. "The greenhouse gas emissions of an electrified vehicle combined with renewable fuels: Life cycle assessment and policy implications," Applied Energy, Elsevier, vol. 289(C).
    7. Huang, Nan & Li, Jiliu & Zhu, Wenbin & Qin, Hu, 2021. "The multi-trip vehicle routing problem with time windows and unloading queue at depot," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Sagar Hossain & Md. Rokonuzzaman & Kazi Sajedur Rahman & A. K. M. Ahasan Habib & Wen-Shan Tan & Md Mahmud & Shahariar Chowdhury & Sittiporn Channumsin, 2023. "Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    2. Zhang, Chao & Yin, Wanjun & Wen, Tao, 2024. "An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid," Energy, Elsevier, vol. 287(C).
    3. Abdelfattah, Wael & Abdelhamid, Ahmed Sayed & Hasanien, Hany M. & Rashad, Basem Abd-Elhamed, 2024. "Smart vehicle-to-grid integration strategy for enhancing distribution system performance and electric vehicle profitability," Energy, Elsevier, vol. 302(C).
    4. Adu-Gyamfi, Gibbson & Asamoah, Ama Nyarkoh & Obuobi, Bright & Nketiah, Emmanuel & Zhang, Ming, 2024. "Electric mobility in an oil-producing developing nation: Empirical assessment of electric vehicle adoption," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    5. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    6. Güven, Aykut Fatih, 2024. "Integrating electric vehicles into hybrid microgrids: A stochastic approach to future-ready renewable energy solutions and management," Energy, Elsevier, vol. 303(C).
    7. 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).
    8. Yin, WanJun & Wen, Tao & Zhang, Chao, 2023. "Cooperative optimal scheduling strategy of electric vehicles based on dynamic electricity price mechanism," Energy, Elsevier, vol. 263(PA).
    9. Hu, Likun & Cao, Yi & Yin, Linfei, 2024. "Fractional-order long-term price guidance mechanism based on bidirectional prediction with attention mechanism for electric vehicle charging," Energy, Elsevier, vol. 293(C).
    10. Yin, Wanjun & Ji, Jianbo, 2024. "Research on EV charging load forecasting and orderly charging scheduling based on model fusion," Energy, Elsevier, vol. 290(C).
    11. Xiong, Yongkang & Zeng, Zhenfeng & Xin, Jianbo & Song, Guanhong & Xia, Yonghong & Xu, Zaide, 2023. "Renewable energy time series regulation strategy considering grid flexible load and N-1 faults," Energy, Elsevier, vol. 284(C).
    12. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M., 2024. "A Bi-level optimization strategy for electric vehicle retailers based on robust pricing and hybrid demand response," Energy, Elsevier, vol. 289(C).

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    Keywords

    Electric vehicle; V2G; Cost; Collaborative optimization;
    All these keywords.

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