The integration of smart grids with Advanced Metering Infrastructure (AMI) has bridged the
realms of the Internet of Vehicles (IoV) and Electric Vehicles (EVs), yet challenges persist in …

An accurate electrical load forecast is essential for the effective implementation of vehicle-to-
grid (V2G) technology to achieve optimal electric vehicle (EV) charging decisions …

In this study, we propose a machine learning (ML) model to predict the availability of an
electric vehicle (EV) providing vehicle to home (V2H) services. Electric vehicles are able to …

Accurate forecast of electric vehicle energy demand is vital for maintaining the stability and
reliability of power systems. With the increasing prevalence of electric vehicles in …

This research work proposes an Improved Supervised Learning (ISL)-based Deep Neural
Network (DNN) for accurately forecasting the load demand of Electric Vehicles (EVs). This …

Electric vehicles (EVs) are advancing the transport sector towards a robust and reliable
carbon-neutral future. Given this increasing uptake of EVs, electrical grids and power …

Electric vehicles (EVs) are inducing revolutionary developments to the transportation and
power sectors. Their innumerable benefits are forcing nations to adopt this sustainable …

This study addresses the challenge of accurately forecasting the energy consumption of
electric vehicles (EVs), which is crucial for reducing range anxiety and advancing strategies …

As the significance of participation in the Day-Ahead Market (DAM) for stakeholders
managing the charging of Electric Vehicle (EV) fleets increases, the necessity for precise EV …

Electric vehicles (EVs) are the future of the automobile industry, as they produce zero
emissions and address environmental and health concerns caused by traditional fuel …