Optimal location and sizing of renewable distributed generations and electric vehicle charging stations

Marina Guindi, Rashad M. Kamel

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Many countries are aiming to replace gasoline-based vehicles with electric vehicles (EVs). The increasing adoption of EVs has led to a surge in the number of charging stations, significantly impacting the electrical grid with issues such as power quality degradation, increased losses, and voltage fluctuations. In response to these challenges, there is a growing interest in integrating distributed generation from unconventional and renewable sources into the grid to power EV Charging Stations (EVCSs). However, this integration poses new complexities, including increased power losses and voltage instability. Consequently, the optimal allocation and sizing of Renewable Distributed Generations (RDGs) and EVCSs have become critical planning considerations. This paper addresses these issues by formulating a multi-objective optimization problem aimed at minimizing power losses and improving the voltage profile of distribution systems. The study introduces several constraints, including the placement of EVCSs and RDGs at separate buses, and employs particle swarm optimization and cuckoo search algorithm to simultaneously determine the optimal locations and sizes of the RDGs and the optimal locations of the EVCSs. The effectiveness of the proposed techniques is demonstrated through simulations on IEEE 33 radial and meshed distribution systems, illustrating their capability to identify optimal configurations for integrating RDGs and EVCSs.

Original languageAmerican English
Article number121272
Pages (from-to)1-22
Number of pages22
JournalRenewable Energy
Volume235
DOIs
StatePublished - 17 Sep 2024

Keywords

  • Cuckoo search algorithm
  • Electric vehicle charging station
  • Particle swarm optimization
  • Renewable distributed generation

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