University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 5 4 2015 02 20 Electric Vehicles Parking (EVP) Sitting Considering GIS Information and the Extent of Urban Areas Electric Vehicles Parking (EVP) Sitting Considering GIS Information and the Extent of Urban Areas 71 84 15402 FA Mohammad R. Aghaebrahimi Faculty of Elec. & Comp. Engineering, University of Birjand, Birjand, Iran Mahdi Tourani Faculty of Elec. & Comp. Engineering, University of Birjand, Birjand, Iran Mohammad M. Ghasemipour Faculty of Elec. & Comp. Engineering, University of Birjand, Birjand, Iran Journal Article 2016 06 14 energy resources, such as wind and solar, are increased. Also, the use of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV), known as V2G, is under development. Due to the widespread use of these vehicles in the near future, Electric Vehicles Parking (EVP) is considered as a source of Distributed Generation (DG) and Electric Energy Storage. The location of parking lot is important for power utilities to reduce power losses, and to municipalities of the urban areas from construction point of view. In this paper, sitting of EVP considering GIS information and the extent of urban areas will be discussed for rapid determination of parking locations using different evolutionary algorithms. The goal is to reduce the candidate locations, to analyze and to compare the performance of these algorithms as well as increasing the satisfaction of power utilities and municipalities. energy resources, such as wind and solar, are increased. Also, the use of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV), known as V2G, is under development. Due to the widespread use of these vehicles in the near future, Electric Vehicles Parking (EVP) is considered as a source of Distributed Generation (DG) and Electric Energy Storage. The location of parking lot is important for power utilities to reduce power losses, and to municipalities of the urban areas from construction point of view. In this paper, sitting of EVP considering GIS information and the extent of urban areas will be discussed for rapid determination of parking locations using different evolutionary algorithms. The goal is to reduce the candidate locations, to analyze and to compare the performance of these algorithms as well as increasing the satisfaction of power utilities and municipalities. https://isee.ui.ac.ir/article_15402_4a047aba808d65cbcc7958f872b0cdf9.pdf