An Adaptive Aggregation Impendence EVs Charging Load Model

    • Presentation speakers

    Charging load modeling for electric vehicles is a fundamental work for most studies related to EVs. However, it is a challenge due to its complexity. This paper proposes a novel EV charging load model which applies the Bayes method to adjust the distribution of the number of EVs starting to charge and predict this number when generating the aggregation impedance model. A study case of a station in Beijing is applied to verify the proposed model. The results show that the model has satisfactory accuracy.


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