Open AccessCost‐based optimal siting and sizing of electric vehicle charging stations considering demand response programmes
Author(s) -
Simorgh Hamid,
DoagouMojarrad Hasan,
Razmi Hadi,
Gharehpetian Gevork B.
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.1663
Subject(s) - sizing , particle swarm optimization , demand response , total cost , cost reduction , mathematical optimization , electric vehicle , grid , computer science , reduction (mathematics) , incentive , grid connection , electricity , reliability engineering , operations research , photovoltaic system , engineering , electrical engineering , mathematics , economics , art , power (physics) , physics , quantum mechanics , visual arts , geometry , management , microeconomics
Here, the optimal placement and sizing of electric vehicle charging stations (EVCSs) are presented. High penetration of electric vehicles (EVs) and resulted losses in network would consequently impose more complexity to solution of application problem of EVCSs. To overcome this problem, the model would consider the incentive‐based demand response programmes (DRPs), which is handled by particle swarm optimisation algorithm. Minimising investment cost, connection cost, total cost of losses, and demand response (DR) cost are the objective functions of this problem here. Finally, the proposed model is applied to a test system and results are discussed. By comparing the results obtained through different scenarios, it is concluded that the application of DRP results in a distinct reduction in grid losses and total costs.