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• W2575527319 abstract "The fast development of smart-grid technologies and applications calls for new means to meet the transportation and environment requirements of the next trend of mainstream vehicles. Electric vehicle (EV), which has been regarded as an important replacement for present gasoline-based vehicle, is expected to greatly reduce the carbon emissions meanwhile offer acceptable transportation ability. However, most of present market-level electric vehicle heavily rely its capacity-constrained battery which can only support limited driving range. Although there have been many pioneer works focusing on ameliorating the driving experience of EVs through tuning the placement of charging infrastructure, most of them do not consider the heterogeneity of vehicle movement in different scenarios. In this paper, starting from a fine-grained analysis of a real-world vehicle trace, a charging station placement algorithm considering the installation cost, traffic flow and battery capacity, called EVReal, is proposed. In comparing its performance with other representative algorithms, EVReal outperforms the others in various metrics." @default.
• W2575527319 created "2017-01-26" @default.
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• W2575527319 date "2016-01-01" @default.
• W2575527319 modified "2023-09-27" @default.
• W2575527319 title "Electrical Vehicle Charging Station Deployment Based on Real World Vehicle Trace" @default.
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• W2575527319 doi "https://doi.org/10.1007/978-3-319-51969-2_5" @default.
• W2575527319 hasPublicationYear "2016" @default.
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