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An IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systems

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dc.contributor.author Chamola, Vinay
dc.date.accessioned 2023-03-16T09:32:44Z
dc.date.available 2023-03-16T09:32:44Z
dc.date.issued 2020-10
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/9153179
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9784
dc.description.abstract The daily fluctuations in the power requirements and the regulation of voltage and frequency cause substantial energy dissipation. These lead to a reduction in the operational efficiency of the power grid. V2G (Vehicle 2 Grid) enabled electric vehicles (EVs) can act as a reactive power resource and can provide active power regulation, load matching, and current harmonic filtering. We propose a smart framework based on Internet of Things (IoT) and Edge computing to manage the V2G operations efficiently. The proposed framework can handle distributed energy sources, and can help in grid stabilization, increasing its reliability, and improving the power efficiency. V2G energy transfers can affect the EV's battery lifetime, however if carefully managed, they can be economical both for the grid operators, as well as the EV owners. The proposed framework creates an optimum charging schedule for each EV to maximize the profit of the EV owners, keeping the preferences set by the vehicle owner and the grid requirement in consideration. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Vehicle-to-Grid(V2G) en_US
dc.subject Grid stabilization en_US
dc.subject Smart model en_US
dc.subject Optimum charging schedule en_US
dc.title An IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systems en_US
dc.type Article en_US


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