An improved coordinated charging method was proposed to deal with numerous electric vehicles' (EVs') uncertainty charging habits in this work, this method is an optimization model taking EVs' charging start time and charging power as the control variables. In the model users' charging habit was represented by Binomial distribution and the EVs' uncertainty charging demand was imitated by the Mento Carlo Simulation (MCS) method. Taking a classical load profile and driving data of Beijing city as example, the effects of uncertainty charging habit, uncertainty charging power to EVs' charging load demand and distribution power load were investigated. Study found that charging start time and charging power can be combined to regulate EVs' charging power load to meet users' charging energy demand as well as reduce the impact charging load on distribution network. After simulating, the superiority of the charging load regulation strategy proposed in this paper was verified.


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    Title :

    Coordinated charging method of electric vehicles to deal with uncertainty factors


    Contributors:
    Yang, Bing (author) / Wang, Li-fang (author) / Liao, Cheng-lin (author) / Ji, Li (author)


    Publication date :

    2014-08-01


    Size :

    783965 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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