TY - GEN
T1 - Optimized renewable energy integration for EV high-power dynamic wireless charging systems
AU - Zeng, Rong
AU - Galigekere, Veda
AU - Onar, Omer
AU - Ozpineci, Burak
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/2/16
Y1 - 2021/2/16
N2 - Dynamic wireless charging for electric vehicles is an emerging technology to reduce on-board battery size and extend driving range. Due to its unique characteristic of vehicle-speed-related pulse-like load profile, the high-power dynamic wireless charging system (DWCS) introduces high stress to the utility grid. In this paper, an optimization model for renewable energy integration in the DWCS is proposed to mitigate the grid impact and minimize the operation costs of the whole system. As the load profile of DWCS is related to the traffic volume and various approaching vehicle speeds, the annual average daily traffic data and a stochastic model are used to develop 24-hour load profile of DWCS. To find a tradeoff between grid impact mitigation and operation costs minimization, relationships among power demand from power grid, photovoltaic (PV) capacity, wind energy (WE) capacity and energy storage (ES) capacity are analyzed, and the optimization objective and constraints are developed. Numerical simulation results demonstrate that energy storage integration can greatly mitigate the grid impact of DWCS, and optimal ratio of PV and WE can significantly reduce the operation cost of DWCS.
AB - Dynamic wireless charging for electric vehicles is an emerging technology to reduce on-board battery size and extend driving range. Due to its unique characteristic of vehicle-speed-related pulse-like load profile, the high-power dynamic wireless charging system (DWCS) introduces high stress to the utility grid. In this paper, an optimization model for renewable energy integration in the DWCS is proposed to mitigate the grid impact and minimize the operation costs of the whole system. As the load profile of DWCS is related to the traffic volume and various approaching vehicle speeds, the annual average daily traffic data and a stochastic model are used to develop 24-hour load profile of DWCS. To find a tradeoff between grid impact mitigation and operation costs minimization, relationships among power demand from power grid, photovoltaic (PV) capacity, wind energy (WE) capacity and energy storage (ES) capacity are analyzed, and the optimization objective and constraints are developed. Numerical simulation results demonstrate that energy storage integration can greatly mitigate the grid impact of DWCS, and optimal ratio of PV and WE can significantly reduce the operation cost of DWCS.
KW - Dynamic wireless charging
KW - Electric vehicle
KW - Grid impact
KW - Renewable energy integration
UR - http://www.scopus.com/inward/record.url?scp=85103452459&partnerID=8YFLogxK
U2 - 10.1109/ISGT49243.2021.9372265
DO - 10.1109/ISGT49243.2021.9372265
M3 - Conference contribution
AN - SCOPUS:85103452459
T3 - 2021 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2021
BT - 2021 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2021
Y2 - 16 February 2021 through 18 February 2021
ER -