A large number of electric vehicles connecting to the distribution grids usually introduce significant fluctuations to the grid and the loads. To solve the problem, guiding the users coordinated charging is proposed. Firstly, the uncontrolled charging power prediction models of electric vehicles are established, and the Monte Carlo method is adopted to simulate the power demands of different electric vehicles, and the influences on the load peak-valley ratios and the voltages and losses of the grid are all analyzed. Then the vehicle responses model considering the time-of-use price is analyzed, and the vehicle response ratios are obtained under different time-of-use prices. Finally the multi-objective optimization model is constructed including the minimum peak-valley ratio, maximum consumption satisfaction index and cost satisfaction index. In the procedure, vehicles and the grid are both taken into account. The results indicate the proposed method could guide the users coordinated charging, and the peak shaving and valley filling is also achieved, and the operation of the distribution grid is improved.


    Access

    Download


    Export, share and cite



    Title :

    The Electric Vehicle Time-of-Use Price Optimization Model Considering the Demand Response


    Contributors:
    Shi Zejing (author) / Zhu Ninghui (author) / Yu Jinsong (author)


    Publication date :

    2018




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Electric vehicle demand response method considering power grid response deviation

    HU ZESHENG / HWU EN-TE / KIM BYEONG CHO et al. | European Patent Office | 2024

    Free access

    Electric vehicle multi-objective optimization scheduling method based on price type demand response

    PANG SONGLING / ZHAO YUNAN / QIN FUYUN | European Patent Office | 2023

    Free access

    Micro-grid optimization operation method and system considering electric vehicle load demand response

    XIA SHIWEI / YUAN LETIAN / CAI LIUYANG et al. | European Patent Office | 2023

    Free access