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

Various electric vehicle charging and discharging strategies (EVs) and V2G technologies
are discussed in this article as their impacts on energy distribution networks. The V2G …

The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …

Electric cars (EVs) are getting more and more popular across the globe. While comparing
traditional utility grid-based EV charging, photovoltaic (PV) powered EV charging may …

The transport sector is experiencing a notable transition towards sustainability, propelled by
technological progress, innovative materials, and a dedication to environmental …

The active participation of electric vehicles (EVs) in both the transportation sector and
energy systems is essential to curb the ever-increasing greenhouse gas emissions. EV …

Electric vehicles (EVs) have emerged as one of the alternative solutions for reducing carbon
emissions in the road transportation sector. In the near future, more and more EVs will be …

Due to the rapid expansion of electric vehicles (EVs), they are expected to be one of the
main contributors to transportation. The increasing use of fossil fuels as one of the most …

This study investigates the techno-economic impacts analysis of renewable energy-based
hybrid energy storage system integrated grid electric vehicles charging station (EVCS) in …

The electrification of the transportation sector is a pivotal stride towards ensuring
sustainability in our systems. This paradigm offers a promising solution to multiple …