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The huge amount of data generated by devices, vehicles, buildings, the power grid, and many other connected things, coupled with increased rates of data transmission, constitute the big data challenge. Among many areas associated with the Internet of Things, smart grid and electric vehilces have their share of this challenge by being both producers and consumers (ie., prosumers) of big data. Electric vehicls can significantly help smart cities to become greener by reducing emissions of the transportation sector and play an important role in green smart cities. In this article, we first survey the data analytics techniques used for handling the big data of smart grid and electric vehicles. The data generated by electric vehicles come from sources that vary from sensors to trip logs. Once this vast amount of data are analyzed using big data techniques, they can be used to develop policies for siting charging stations, developing smart charging algorithms, solving energy efficiency issues, evaluating the capacity of power distribution systems to handle extra charging loads, and finally, determining the market value for the services provided by electric vehicles (i.e., vehicle-to-grid opportunities). This article provides a comprehensive overview of the data analytics landscape on the electric vehicle integration to green smart cities. It serves as a roadmap to the future data analytics needs and solutions for electric vehicle integration to smart cities.
Li et al. (Wed,) studied this question.