TY - GEN
T1 - Charging Station Placement for Electric Vehicles
AU - Pawar, Suyash
AU - Kalkhambkar, Vaiju
AU - Kumar, Rajesh
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The increased CO2 emissions are the major environmental concerns of the 21st century. The transportation sector is one of the key players in the degradation of air quality. Electric vehicles (EVs) are suitable alternatives to deal with emission problems. To adopt EVs on a large scale, proper charging infrastructure is very important. In this work, a novel approach is proposed for the placement and sizing of EV charging stations considering both transport and distribution networks. This paper presents a two-stage planning model for the sizing and placement of EV charging stations. In the first stage, candidate locations are identified using the technique for order preference by similarity to the ideal solution (TOPSIS) method. In the second stage, optimal locations for EV charging stations are obtained by optimization technique, particle swarm optimization algorithm (PSO) and grey wolf optimization (GWO) is utilized to find optimal locations. Results of PSO & GWO are compared, it is observed that GWO gives slightly better results than PSO. Also, GWO converged in less iteration. Optimization result gives the size of the charging station and no. of fast and slow chargers. Power loss in the distribution grid, accessibility of charging station, and road traffic, cost of charging station are considered for optimal sizing and allocation of the EV charging station.
AB - The increased CO2 emissions are the major environmental concerns of the 21st century. The transportation sector is one of the key players in the degradation of air quality. Electric vehicles (EVs) are suitable alternatives to deal with emission problems. To adopt EVs on a large scale, proper charging infrastructure is very important. In this work, a novel approach is proposed for the placement and sizing of EV charging stations considering both transport and distribution networks. This paper presents a two-stage planning model for the sizing and placement of EV charging stations. In the first stage, candidate locations are identified using the technique for order preference by similarity to the ideal solution (TOPSIS) method. In the second stage, optimal locations for EV charging stations are obtained by optimization technique, particle swarm optimization algorithm (PSO) and grey wolf optimization (GWO) is utilized to find optimal locations. Results of PSO & GWO are compared, it is observed that GWO gives slightly better results than PSO. Also, GWO converged in less iteration. Optimization result gives the size of the charging station and no. of fast and slow chargers. Power loss in the distribution grid, accessibility of charging station, and road traffic, cost of charging station are considered for optimal sizing and allocation of the EV charging station.
KW - charging station
KW - distribution network
KW - gwo
KW - pso
KW - superimposition
KW - transportation network
UR - http://www.scopus.com/inward/record.url?scp=85152394574&partnerID=8YFLogxK
U2 - 10.1109/PEDES56012.2022.10080514
DO - 10.1109/PEDES56012.2022.10080514
M3 - Conference contribution
AN - SCOPUS:85152394574
T3 - 10th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2022
BT - 10th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2022
Y2 - 14 December 2022 through 17 December 2022
ER -