Optimal planning strategy for charging and discharging an electric vehicle connected to the grid through wireless recharger

The increasing number of electric Vehicles (EVs) and their influence on the power grid present difficulties that this article addresses by suggesting optimal planning methods for EV charging and discharging. EV charging and discharging operations are effectively managed by creating both locally and globally optimal planning schemes. Future transportation could be changed by the widespread adoption of dynamic wireless power transfer systems in conjunction with EVs, as they would enable speedier travel and continuous EV battery recharging. Dynamic wireless power transfer is a practical answer to problems with electric vehicles. The electrification of automobiles will have a significant influence on the power infrastructure due to the increase in demand for electricity. In this study, we provide an optimal planning method worldwide and a locally optimal strategy for EV charging and discharging. To minimize the total cost of all EVs that charge and discharge during the day, we propose an optimization problem for global planning in which the charging powers are optimized. The simulation results demonstrate that the proposed planning schemes can effectively reduce the total electricity cost for EV owners while also minimizing the impact on the power grid. The globally optimal planning scheme achieves the lowest electricity cost, while the locally optimal scheme provides a good balance between cost reduction and computational complexity.

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Publication Details

Journal
Frontiers in Energy Research
Published
2024-09-05
DOI
https://doi.org/10.3389/fenrg.2024.1453711
Citations
1
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.20

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article

Optimal planning strategy for charging and discharging an electric vehicle connected to the grid through wireless recharger

Abdulaziz A. Alkuhayli, Rahmat Ullah, Aymen Flah, Claude Ziad El‐Bayeh et al.
1 citations
Frontiers in Energy Research
Advanced Battery Technologies Research
0.20
article

Optimal planning strategy for charging and discharging an electric vehicle connected to the grid through wireless recharger

Abdulaziz A. Alkuhayli, Rahmat Ullah, Aymen Flah, Claude Ziad El‐Bayeh, Asma Boukhchana
article en
1 citations

Abstract

The increasing number of electric Vehicles (EVs) and their influence on the power grid present difficulties that this article addresses by suggesting optimal planning methods for EV charging and discharging. EV charging and discharging operations are effectively managed by creating both locally and globally optimal planning schemes. Future transportation could be changed by the widespread adoption of dynamic wireless power transfer systems in conjunction with EVs, as they would enable speedier travel and continuous EV battery recharging. Dynamic wireless power transfer is a practical answer to problems with electric vehicles. The electrification of automobiles will have a significant influence on the power infrastructure due to the increase in demand for electricity. In this study, we provide an optimal planning method worldwide and a locally optimal strategy for EV charging and discharging. To minimize the total cost of all EVs that charge and discharge during the day, we propose an optimization problem for global planning in which the charging powers are optimized. The simulation results demonstrate that the proposed planning schemes can effectively reduce the total electricity cost for EV owners while also minimizing the impact on the power grid. The globally optimal planning scheme achieves the lowest electricity cost, while the locally optimal scheme provides a good balance between cost reduction and computational complexity.

Frontiers in Energy ResearchVol. 12
Applied Science Private University (JO), King Saud University (SA), University of Gabès (TN), Cardiff University (GB), Middle East University (JO)
King Saud University
Openalex Percentile: Top 51%
Advanced Battery Technologies Research
0.20
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