Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …

Electric vehicles (EVs) are universally recognized as an incredibly effective method of
lowering gas emissions and dependence on oil for transportation. Electricity, rather than …

As the smart grid evolves, it requires increasing distributed intelligence, optimization and
control. Model predictive control (MPC) facilitates these functionalities for smart grid …

Vehicles around the world are being converted to electric power in order to combat climate
change and lower pollution levels. Sustaining this process calls for more electric vehicle …

The population of electric vehicles (EVs) has grown rapidly over the past decade due to the
development of EV technologies, battery materials, charger facilities, and public charging …

Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …

The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …

This paper presents an optimised bidirectional Vehicle-to-Grid (V2G) operation, based on a
fleet of Electric Vehicles (EVs) connected to a distributed power system, through a network of …

As a result of fossil fuel prices and the associated environmental issues, electric vehicles
(EVs) have become a substitute for fossil-fueled vehicles. Their use is expected to grow …

The unprecedented proliferation of electric vehicles is envisioned to revolutionize the
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …