TY - JOUR
T1 - Placement and Capacity of EV Charging Stations by Considering Uncertainties with Energy Management Strategies
AU - Ahmad, Fareed
AU - Iqbal, Atif
AU - Asharf, Imtiaz
AU - Marzband, Mousa
AU - Khan, Irfan
N1 - Funding information: This publication was made possible by NPRP grant #
[NPRP-13S-0108-20008] from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. In addition, this work was supported from DTE Network+ funded by EPSRC grant reference EP/S032053/1.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - At the present context, Plug-in electric vehicles (PEVs) are gaining popularity in the automotive industry due to their low CO2 emissions, simple maintenance, and low operating costs. As the number of PEVs on the road increases, the charging demand of PEVs affects distribution network features, such as power loss, voltage profile, and harmonic distortion. Furthermore, one more problem arises due to the high peak power demand from the grid to charge the PEVs at the charging station (CS). In addition, the location of CS also affects the behavior of EV users and CS investors. Hence, this paper applies CS investor, PEV user, and distribution network operator who could approach to CS's optimal location and capacity. Integrating renewable energy sources (RESs) at the charging station is suggested to lower the energy stress on the grid. Moreover, to keep down the peak power demand from the grid and utilize renewable energy more efficiently, energy management strategies (EMS) have been applied through the control of charging and discharging of the battery storage system (BSS). In addition, vehicle to grid (V2G) strategy is also applied to discharge the EV battery at charging station. Furthermore, the uncertainties related to PEV charging demand and PV power generation are addressed by the Monte Carlo Simulation (MCS) method.
AB - At the present context, Plug-in electric vehicles (PEVs) are gaining popularity in the automotive industry due to their low CO2 emissions, simple maintenance, and low operating costs. As the number of PEVs on the road increases, the charging demand of PEVs affects distribution network features, such as power loss, voltage profile, and harmonic distortion. Furthermore, one more problem arises due to the high peak power demand from the grid to charge the PEVs at the charging station (CS). In addition, the location of CS also affects the behavior of EV users and CS investors. Hence, this paper applies CS investor, PEV user, and distribution network operator who could approach to CS's optimal location and capacity. Integrating renewable energy sources (RESs) at the charging station is suggested to lower the energy stress on the grid. Moreover, to keep down the peak power demand from the grid and utilize renewable energy more efficiently, energy management strategies (EMS) have been applied through the control of charging and discharging of the battery storage system (BSS). In addition, vehicle to grid (V2G) strategy is also applied to discharge the EV battery at charging station. Furthermore, the uncertainties related to PEV charging demand and PV power generation are addressed by the Monte Carlo Simulation (MCS) method.
KW - battery storage system
KW - charging infrastructure
KW - electric vehicle
KW - energy management strategy
KW - Optimal deployment
UR - http://www.scopus.com/inward/record.url?scp=85149881542&partnerID=8YFLogxK
U2 - 10.1109/tia.2023.3253817
DO - 10.1109/tia.2023.3253817
M3 - Article
SN - 0093-9994
VL - 59
SP - 3865
EP - 3874
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 3
ER -
