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- W4385689110 abstract "Utilizing renewable energy sources (RES) simultaneously eliminates the need for an energy storage system (ESS), reducing overall cost. This research paper focuses on developing an algorithm for efficiently scheduling electric vehicles (EVs) charging at a charging station. The Monte Carlo Method has been used to generate the arrival times of EVs at the station for each time slot. The algorithm consists of two main components: The Vehicle Acceptance Algorithm (VAA) and the Vehicle Scheduling Algorithm (VSA). Accepted vehicles can engage in Vehicle-to-Vehicle (V2V) charging once their State of Charge (SOC) reaches a certain level. Renewable power is supplied through a combination of solar and wind energy. Upon arrival at the charging station, EVs are scheduled based on the available energy at that particular time slot, which includes the remaining energy from RES, the V2V energy of previously scheduled vehicles, and the charger's availability. In cases where there is an energy shortage during a timeslot, EV owners can charge their vehicles using grid power. In order to promote social welfare among EV owners who prefer charging with RES, certain incentives are provided alongside the low cost of charging from renewable sources." @default.
- W4385689110 created "2023-08-10" @default.
- W4385689110 creator A5014445075 @default.
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- W4385689110 date "2023-06-15" @default.
- W4385689110 modified "2023-09-27" @default.
- W4385689110 title "Coordinate Scheduling of Plug-in Electric Vehicles at Charging Station Fed by Renewable Energy Sources" @default.
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- W4385689110 doi "https://doi.org/10.1109/icepe57949.2023.10201636" @default.
- W4385689110 hasPublicationYear "2023" @default.
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