In order to reduce the peak-valley difference of power grid load to improve the stability of power grid, and fully consider the impact of time-of-use electricity price and carbon income, an electric vehicle peak shaving strategy based on improved wild dog optimization algorithm is proposed. Firstly, a peak-shaving model of electric vehicles is established, which comprehensively considers the peak-valley difference of load, the charging cost of electric vehicles, the discharge income of electric vehicles and the income obtained by selling carbon quotas. The charging and discharging power, battery capacity and charging and discharging quantity of electric vehicles are taken as constraints. An improved Dingo Optimization Algorithm (IDOA) is designed to improve the optimization accuracy and speed up the optimization, and IDOA is used to solve the electric vehicle peak shaving model. Finally, the proposed electric vehicle peaking strategy is simulated and verified. The results show that the IDOA algorithm is feasible and efficient. The proposed peaking model reduces the peak-valley difference of the grid load. For electric vehicle owners, it can reduce costs and obtain more benefits.


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    Titel :

    Research on Peaking Strategy of Electric Vehicle Based on Improved Dingo Optimization Algorithm


    Beteiligte:
    Cai, Xinlei (Autor:in) / Guo, Yufei (Autor:in) / Zhu, Jinzhou (Autor:in) / Wu, Longteng (Autor:in)


    Erscheinungsdatum :

    09.05.2024


    Format / Umfang :

    5021260 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch