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 …

Residential electric vehicle (REV) is an advanced technology with a rapid growth rate in
transportation and electric grids. One key challenge in the operation of REVs is the necessity …

The use of electric vehicles (EVs) load management is relevant to support electricity demand
softening, making the grid more economic, efficient, and reliable. However, the absence of …

The high penetration of electric vehicles (EVs) will burden the existing power delivery
infrastructure if their charging and discharging are not adequately coordinated. Dynamic …

The ongoing electrification of mobility comes with the challenge of charging electric vehicles
(EVs) sufficiently while charging infrastructure capacities are limited. Smart charging …

Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …

Due to the participation of large-scale electric vehicles (EVs) in Vehicle-to-Grid (V2G)
services, V2G dispatch centers need to predict the charging and discharging (C&D) loads of …

Electric vehicles (EVs) are viewed as an attractive option to reduce carbon emission and fuel
consumption, but the popularization of EVs has been hindered by the cruising range …

The increasing penetration rate of electric vehicles, associated with a growing charging
demand, could induce a negative impact on the electric grid, such as higher peak power …

Abstract Plug-in Electric Vehicles (PEVs) have gained the user's attention due to their smart
and cost-effective and environment-friendly services. With many benefits, the PEVs services …