128 / 2022-07-04 23:30:59
Forecast of Load Aggregator Dispatchable Potential for Counting and Vehicle Network Interaction
终稿
Rui Feng / Nanjing Normal University
zhaokang yan / Nanjing Normal University
Ruiqi Lu / Nanjing Normal University
Jianwei Xu / Nanjing Normal University
Cong Gao / Nanjing Normal University
Jingwen Shen / Nanjing Normal Universal
Haoran Ge / nanjing normal university
Gang Ma / Nanjing Normal University
In the day-ahead market, load aggregators can participate in market-based trading through rational scheduling of EV charging and discharging. This paper investigates the method to predict the dispatchable potential of electrical vehicle (EV) clusters under the vehicle network interaction. Firstly, a Monte Carlo method was used to simulate the charging and discharging load characteristics of EV clusters; secondly, based on the Minkowski summation Virtual Battery (VB) model, a large-scale single EV storage model is converted into a virtual storage cluster to obtain the maximum charging and discharging power and electric energy boundaries of EV clusters at a time, which can be applied by load aggregators to implement different vehicle-grid interaction strategies and to participate in day-ahead market transactions.
重要日期
  • 会议日期

    11月03日

    2022

    11月05日

    2022

  • 08月01日 2022

    初稿截稿日期

  • 11月04日 2022

    注册截止日期

  • 11月05日 2022

    报告提交截止日期

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