TY - GEN
T1 - Optimizing the Charging Process of Electric Vehicles in the Context of Renewable Energy Integration
AU - Sharida, Ali
AU - Bayindir, Abdullah Berkay
AU - Bayhan, Sertac
AU - Abu-Rub, Haitham
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper proposes a method for optimizing the charging process of electric vehicles (EVs) within the context of renewable energy integration. The proposed method continuously monitors the maximum available power from the renewable energy sources (RES), grid conditions, and EV’s requirements. Upon receiving reference charging or power signals from the connected EV, the system computes the surplus or required power and adjusts grid interaction accordingly. The proposed method offers several advantages. Firstly, it optimizes energy harvesting from RESs by dynamically adjusting grid and EV interactions based on real-time monitoring. Secondly, it enhances grid stability by intelligently controlling power flow, injecting or consuming surplus power in response to the grid condition. Thirdly, it leverages the growing number of EVs connected to the grid, effectively utilizing them as distributed energy storage systems. To validate the effectiveness and efficiency of the proposed method, extensive simulation tests are conducted under diverse scenarios.
AB - This paper proposes a method for optimizing the charging process of electric vehicles (EVs) within the context of renewable energy integration. The proposed method continuously monitors the maximum available power from the renewable energy sources (RES), grid conditions, and EV’s requirements. Upon receiving reference charging or power signals from the connected EV, the system computes the surplus or required power and adjusts grid interaction accordingly. The proposed method offers several advantages. Firstly, it optimizes energy harvesting from RESs by dynamically adjusting grid and EV interactions based on real-time monitoring. Secondly, it enhances grid stability by intelligently controlling power flow, injecting or consuming surplus power in response to the grid condition. Thirdly, it leverages the growing number of EVs connected to the grid, effectively utilizing them as distributed energy storage systems. To validate the effectiveness and efficiency of the proposed method, extensive simulation tests are conducted under diverse scenarios.
KW - Bi-directional EV chargers
KW - EV power flow control
KW - G2V
KW - V2G
KW - charging process optimization
UR - http://www.scopus.com/inward/record.url?scp=105000838494&partnerID=8YFLogxK
U2 - 10.1109/IECON55916.2024.10905323
DO - 10.1109/IECON55916.2024.10905323
M3 - Conference contribution
AN - SCOPUS:105000838494
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society, Proceedings
PB - IEEE Computer Society
T2 - 50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024
Y2 - 3 November 2024 through 6 November 2024
ER -