Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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New Prediction of the Number of Charging Electric Vehicles Using Transformation Matrix and Monte-Carlo Method

  • Go, Hyo-Sang (College of Information and Communication Engineering, Sungkyunkwan University) ;
  • Ryu, Joon-Hyoung (KRRI(Korea Railroad Research Institute)) ;
  • Kim, Jae-won (KRRI(Korea Railroad Research Institute)) ;
  • Kim, Gil-Dong (KRRI(Korea Railroad Research Institute)) ;
  • Kim, Chul-Hwan (College of Information and Communication Engineering, Sungkyunkwan University)
  • Received : 2016.03.23
  • Accepted : 2016.08.11
  • Published : 2017.01.02
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Abstract

An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

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