TY - JOUR
T1 - Placement of electric vehicle fast charging stations in distribution network considering power loss, land cost, and electric vehicle population
AU - Ahmad, Fareed
AU - Iqbal, Atif
AU - Ashraf, Imtiaz
AU - Marzband, Mousa
AU - Khan, Irfan
N1 - Funding information:
This work was supported by the Qatar National Research Fund [13S-0108-20008].
PY - 2022/3/31
Y1 - 2022/3/31
N2 - Recently, electric vehicles (EVs) gained tremendous attention from government agencies and the automotive industry due to lower CO2 emissions, low maintenance, and operating costs. However, due to increasing EV penetration, the EV’s load affects the distribution network parameters like power loss, voltage profile, and harmonic distortion. Therefore, the proper placement of EV fast-charging stations (FCSs) is required for the reliability of the distribution network. Further, this paper proposes two-stage processes for the placement of FCSs. In the first stage, the charging station owner decision index (CSODI) has been introduced considering the land cost index (LCI) and electric vehicle flow index (EVFI). The CSODI has been formulated to minimize the land cost and maximize the EVs flow for FCSs placement. In the next stage, an optimization problem is formulated for minimizing the total active power loss by considering the distribution system operator (DSO) constraints. In addition, the minimization problem has been solved using the hybrid gray wolf optimization-particle swarm optimization (GWOPSO) algorithm. Therefore, the best possible locations were obtained by the GWOPSO with 198.93 kW power loss. Furthermore, the average 2.02% power loss for the GWOPSO technique is lower when compared to the PSO technique.
AB - Recently, electric vehicles (EVs) gained tremendous attention from government agencies and the automotive industry due to lower CO2 emissions, low maintenance, and operating costs. However, due to increasing EV penetration, the EV’s load affects the distribution network parameters like power loss, voltage profile, and harmonic distortion. Therefore, the proper placement of EV fast-charging stations (FCSs) is required for the reliability of the distribution network. Further, this paper proposes two-stage processes for the placement of FCSs. In the first stage, the charging station owner decision index (CSODI) has been introduced considering the land cost index (LCI) and electric vehicle flow index (EVFI). The CSODI has been formulated to minimize the land cost and maximize the EVs flow for FCSs placement. In the next stage, an optimization problem is formulated for minimizing the total active power loss by considering the distribution system operator (DSO) constraints. In addition, the minimization problem has been solved using the hybrid gray wolf optimization-particle swarm optimization (GWOPSO) algorithm. Therefore, the best possible locations were obtained by the GWOPSO with 198.93 kW power loss. Furthermore, the average 2.02% power loss for the GWOPSO technique is lower when compared to the PSO technique.
KW - optimal placement
KW - gray wolf optimization
KW - Land Cost Index
KW - electric vehicle population
KW - Fast-charging stations
UR - http://www.scopus.com/inward/record.url?scp=85127260644&partnerID=8YFLogxK
U2 - 10.1080/15567036.2022.2055233
DO - 10.1080/15567036.2022.2055233
M3 - Article
SN - 1556-7036
VL - 44
SP - 1693
EP - 1709
JO - Energy Sources, Part A: Recovery, Utilization and Environmental Effects
JF - Energy Sources, Part A: Recovery, Utilization and Environmental Effects
IS - 1
ER -