Placement of electric vehicle fast charging stations in distribution network considering power loss, land cost, and electric vehicle population

Fareed Ahmad*, Atif Iqbal, Imtiaz Ashraf, Mousa Marzband, Irfan Khan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)1693-1709
Number of pages17
JournalEnergy Sources, Part A: Recovery, Utilization and Environmental Effects
Volume44
Issue number1
Early online date24 Mar 2022
DOIs
Publication statusPublished - 31 Mar 2022

Keywords

  • optimal placement
  • gray wolf optimization
  • Land Cost Index
  • electric vehicle population
  • Fast-charging stations

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