This paper presents a forecasting model to estimate electric vehicle charging demand based
on big data technologies. Most previous studies have not considered real-world traffic …

With the widespread use of electric vehicles, their charging power demand has increased
and become a significant burden on power grids. The uncoordinated deployment of electric …

This study compared the methods used to forecast increases in power consumption caused
by the rising popularity of electric vehicles (EVs). An excellent model for each region was …

More and more adoptions of electric vehicles (EVs) would bring a potential threat on the
existing electric grid. In this context, a systematic methodology is presented in this paper to …

In this paper, multiple featured machine learning algorithms and deep learning algorithms
are applied in forecasting the electric vehicles charging load profile from real datasets of …

The accurate estimation and prediction of charging demand play an essential role in
charging infrastructure planning, power grid laying and efficient operations. In this paper …

In the paper, an electric vehicle (EV) charging load prediction approach considering vehicle
types is developed. The GM (1, 1) model is initially introduced to estimate the ownership of …

Electric vehicles (EVs) are the most important components of smart transportation systems.
Limited driving range, prolonged charging times, and inadequate charging infrastructure are …

Electric vehicle (EV) has been popularized and promoted on a large scale because of its
clean and efficient features. Charging this increasing number of EVs is expected to have an …

Load forecasting is one of the major challenges of power system operation and is crucial to
the effective scheduling for economic dispatch at multiple time scales. Numerous load …