Journal of Electrical Engineering and Technology

  • 제8권2호
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  • Pages.244-251
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  • 2013
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  • 1975-0102(pISSN)
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  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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Impact of Electric Vehicle Penetration-Based Charging Demand on Load Profile

  • Park, Woo-Jae (School of Electrical and Electronic Eng., Yonsei University) ;
  • Song, Kyung-Bin (Department of Electrical Engineering, Soongsil University) ;
  • Park, Jung-Wook (Department of Electrical Engineering, Soongsil University)
  • 투고 : 2012.04.13
  • 심사 : 2012.09.13
  • 발행 : 2013.03.01
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초록

This paper presents a study the change of the load profile on the power system by the charging impact of electric vehicles (EVs) in 2020. The impact of charging EVs on the load demand is determined not only by the number of EVs in usage pattern, but also by the number of EVs being charged at once. The charging load is determined on an hourly basis using the number of the EVs based on different scenarios considering battery size, model, the use of vehicles, charging at home or work, and the method of charging, which is either fast or slow. Focusing on the impact of future load profile in Korea with EVs reaching up 10 and 20 percentage, increased power demand by EVs charging is analyzed. Also, this paper analyzes the impact of a time-of-use (TOU) tariff system on the charging of EVs in Korea. The results demonstrate how the penetration of EVs increases the load profile and decreases charging demand by TOU tariff system on the future power system.

키워드

참고문헌

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피인용 문헌

  1. A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects vol.49, 2015, https://doi.org/10.1016/j.rser.2015.04.130
  2. Bi-directional electric vehicle fast charging station with novel reactive power compensation for voltage regulation vol.64, 2015, https://doi.org/10.1016/j.ijepes.2014.07.025
  3. Electric vehicle charging demand forecasting model based on big data technologies vol.183, 2016, https://doi.org/10.1016/j.apenergy.2016.08.080
  4. Spacial and dynamic energy demand of the E39 highway – Implications on electrification options vol.195, 2017, https://doi.org/10.1016/j.apenergy.2017.02.025
  5. Prediction of electric vehicle charging-power demand in realistic urban traffic networks vol.195, 2017, https://doi.org/10.1016/j.apenergy.2017.02.021