As a promising mobility tool in future transportation systems, Electric Vehicle (EV) has environment-friendly benefits compared with traditional internal-combustion-engine vehicle. However, uncoordinated charging of mass EVs bring huge burden to power grids. To tackle this problem, a coordinated charging strategy of EVs is necessary. EV aggregator could play as a coordinator between EV owner and power grids, both meeting owner driving requirements and power grids operation requirements. However, a owner-aggregator economic inconsistency issue appears, that is EV owner get a higher charging cost in aggregator scheduling than self scheduling. In order to mediate owner-aggregator economic inconsistency issue, this paper designed a centralized two-stage EVs charging/discharging scheduling strategy in a residential community within 24 hours from the viewpoint of two stakeholders: EV owners (to minimize each EV owner charging cost) and aggregator (to maximize aggregator revenue). In the first-stage, EVs operation are scheduled from EV owners viewpoint, to obtain the minimal charging cost for each EV owner. Then, in the second-stage, the scheduling results in the first-stage are involved as constraints. The objective in the second-stage is to maximize aggregator revenue, without sacrificing each EV owner's economic benefit (no charging cost increment). A rebate factor is introduced in this model, which is the pay back for each EV owner provided by aggregator. Case study shows the effectiveness of the proposed scheduling strategy: the aggregator revenue is maximized without sacrificing each EV owner's economic benefit so that owner-aggregator economic inconsistency issue is mediated. The impact parameter of rebate factor in aggregator revenue in analyzed.


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    Title :

    A two-stage electric vehicles scheduling strategy to address economic inconsistency issues of stakeholders


    Contributors:
    Han, Bing (author) / Lu, Shaofeng (author) / Xue, Fei (author) / Jiang, Lin (author) / Zhu, Huaiying (author)


    Publication date :

    2017-06-01


    Size :

    266134 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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