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PANG Pei-chuan, ZENG Cheng, YANG Biao, ZHANG Qian, Calculation of Electric Vehicles Charging Load by Monte Carlo Simulation Method. Telecom Power Technology, 2016, 33(1).

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Article

Influence and Strategy of Electric Vehicle Charging on Distribution Network Voltage Based on Uncertainty Charging Habit

1School of Electrical Engineering and Automation, Nanjing Normal University


Journal of Automation and Control. 2017, Vol. 5 No. 1, 20-24
DOI: 10.12691/automation-5-1-4
Copyright © 2017 Science and Education Publishing

Cite this paper:
Lu Mengtian. Influence and Strategy of Electric Vehicle Charging on Distribution Network Voltage Based on Uncertainty Charging Habit. Journal of Automation and Control. 2017; 5(1):20-24. doi: 10.12691/automation-5-1-4.

Correspondence to: Lu  Mengtian, School of Electrical Engineering and Automation, Nanjing Normal University. Email: lmt666@icloud.com

Abstract

With the increasing scale of the use of electric vehicles, impact of electric vehicle charging on the distribution system cannot be ignored. Considering uncertainty in the charging behavior, large-scale disorderly charging will cause the voltage deviation of distribution network exceeds the specified value. In the paper, based on the IEEE33 node as an example, the goal is to minimum each node voltage deviation by to controlling charge power, considering the constraints of the charging energy and the charging time, and optimized by the genetic algorithm. By using Newton Raphson power flow method, the voltage offset of each node before and after optimization is obtained, and the effectiveness of the charging load optimization model is verified by comparing and analyzing.

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