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- W4312949258 abstract "Nowadays power demands penetration increasing day by day due to the global adaptation of Electric Vehicles (EVs). It has been observed that a rising penetration rate of electric vehicles (EVs) fleet could cause undervoltage and congestions in the power grid network. Under such circumstances, optimal scheduling of EVs charging/discharging power proved to be one of the best alternatives. The prime objective of this paper, to investigate the impact of charging and discharging on load variations/peaks. This paper develops a load estimation model and EVs charging model under the various scenario of vehicle travelling patterns to predict their impacts on charging behavior. This paper also demonstrates a Markov Chain Monte Carlo (MCMC) based charging/discharging algorithm that efficiently deals with the prediction of EVs driving patterns and manages the issues of high-power demand during peak time. In vehicle to grid (V2G) technologies, the stored energy supplies power to the grid at a certain time when required. Further, to increase the flexibility of the grid storage system and user trip schedule using a proposed algorithm. The proposed probabilistic approach demonstrates an effective estimation of power demands and controls the peak regulation, without changing the performance of the scheduled vehicle owner's trip." @default.
- W4312949258 created "2023-01-05" @default.
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- W4312949258 date "2021-12-16" @default.
- W4312949258 modified "2023-10-11" @default.
- W4312949258 title "Optimal Scheduling of Charging/Discharging Power and EVs Pattern Using Stochastic Techniques in V2G System" @default.
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- W4312949258 doi "https://doi.org/10.1109/itec-india53713.2021.9932455" @default.
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