Engr. Mariz B. Arias of the Department of Electrical Engineering of the Faculty of Engineering co-published a research paper entitled 鈥淓lectric vehicle charging demand forecasting model based on big data technologies鈥� in the journal Applied Energy (2016 鈥� 183, pages 327-339). Her co-author is Sungwoo Bae of Yeungnam University, South Korea.
Considering that 鈥淢ost previous studies have not considered real-world traffic distribution data and weather conditions in predicting the electric vehicle charging demand, the paper used historical traffic data and weather data of South Korea to formulate the forecasting model.鈥�
According to Arias and Bae, 鈥渢he presented forecasting model may allow power system engi- neers to anticipate electric vehicle charging demand based on historical traffic data and weather data. Therefore, the proposed electric vehicle charging demand model can be the foundation for the research on the impact of charging electric vehicles on the power system.鈥�
The article may be accessed via .
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