Title :
Methodology for optimizing the number of electric vehicles deployed under a smart grid
Author :
Kumar, K. Nandha ; Sivaneasan, B. ; So, P.L. ; Wang, D.Z.W.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
One of the major sources of greenhouse gasses (GHG) is the transportation sector. Electrification of transportation is generally considered as the optimal solution for decreasing GHG emissions of the transportation sector. Although there are various obstacles for the deployment of electric vehicles (EVs), unavailability of charging infrastructure is the biggest obstacle. In this paper, a methodology is proposed for the estimation of the optimal number of EVs that can be deployed under a given smart grid. Monte-carlo simulations and linear programming are used for the estimation. The methodology is applied to calculate the optimal number of EVs that can be deployed under a high-rise building in Singapore. The method is validated using load demand data of 5 years, load model of EVs and EV load scheduling. The cost-benefit analysis for the installation of charging stations in buildings is also discussed by varying different parameters.
Keywords :
Monte Carlo methods; air pollution control; battery powered vehicles; cost-benefit analysis; linear programming; scheduling; smart power grids; EV deployment; EV load model; EV load scheduling; EV optimal number estimation; GHG emissions; Monte-carlo simulation; Singapore; charging infrastructure; charging station installation; cost-benefit analysis; electric vehicle deployment; electric vehicle number optimization; greenhouse gas source; high-rise building; linear programming; smart grid; transportation electrification; transportation sector; Buildings; Educational institutions; Estimation; Linear programming; Smart grids; Vehicles; Monte-carlo simulations; cost-benefit analysis; electric vehicles; linear programming;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6699885