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dc.contributor.authorChamola, Vinay-
dc.date.accessioned2023-03-16T09:32:44Z-
dc.date.available2023-03-16T09:32:44Z-
dc.date.issued2020-10-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/9153179-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9784-
dc.description.abstractThe 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.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectVehicle-to-Grid(V2G)en_US
dc.subjectGrid stabilizationen_US
dc.subjectSmart modelen_US
dc.subjectOptimum charging scheduleen_US
dc.titleAn IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systemsen_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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