Hierarchical operation of electric vehicle charging station in smart grid integration applications—An overview

Y Wu, Z Wang, Y Huangfu, A Ravey, D Chrenko… - International Journal of …, 2022 - Elsevier
With the fast development of electrifications of vehicles, EV charging stations are booming in
coming years. Meanwhile, the growing demand for charging power, and the stochastic …

Fast-charging station for electric vehicles, challenges and issues: A comprehensive review

A Ghasemi-Marzbali - Journal of Energy Storage, 2022 - Elsevier
In recent years, many countries have set specific goals to replace fossil fuel vehicles with the
electric ones due to environmental concerns and issues related to energy supply security; it …

ANTi-Vax: a novel Twitter dataset for COVID-19 vaccine misinformation detection

K Hayawi, S Shahriar, MA Serhani, I Taleb, SS Mathew - Public health, 2022 - Elsevier
Abstract Objectives COVID-19 (SARS-CoV-2) pandemic has infected hundreds of millions
and inflicted millions of deaths around the globe. Fortunately, the introduction of COVID-19 …

Reinforcement learning based EV charging management systems–a review

HM Abdullah, A Gastli, L Ben-Brahim - IEEE Access, 2021 - ieeexplore.ieee.org
To mitigate global warming and energy shortage, integration of renewable energy
generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been …

[PDF][PDF] The role of artificial intelligence in the mass adoption of electric vehicles

M Ahmed, Y Zheng, A Amine, H Fathiannasab, Z Chen - Joule, 2021 - cell.com
The electrification of mass transportation is hailed as a solution for reducing global
greenhouse-gas emissions and dependence on unsustainable energy sources. The annual …

Prediction of EV charging behavior using machine learning

S Shahriar, AR Al-Ali, AH Osman, S Dhou… - Ieee …, 2021 - ieeexplore.ieee.org
As a key pillar of smart transportation in smart city applications, electric vehicles (EVs) are
becoming increasingly popular for their contribution in reducing greenhouse gas emissions …

When smart cities get smarter via machine learning: An in-depth literature review

SS Band, S Ardabili, M Sookhak… - IEEE …, 2022 - ieeexplore.ieee.org
The manuscript represents a comeprehensive and systematic literature review on the
machine learning methods in the emerging applications of the smart cities. Application …

A V2G-oriented reinforcement learning framework and empirical study for heterogeneous electric vehicle charging management

X Hao, Y Chen, H Wang, H Wang, Y Meng… - Sustainable Cities and …, 2023 - Elsevier
Abstract Vehicle-to-grid (V2G) technology is a promising solution to energy supply security
issues associated with future electric grids. A decisive factor to successful V2G is effective …

Predictive machine learning in optimizing the performance of electric vehicle batteries: Techniques, challenges, and solutions

VS Naresh, GV Ratnakara Rao… - … Reviews: Data Mining …, 2024 - Wiley Online Library
This research paper explores the importance of optimizing the performance of electric
vehicle (EV) batteries to align with the rapid growth in EV usage. It uses predictive machine …

Research trends, themes, and insights on artificial neural networks for smart cities towards SDG-11

A Jain, IH Gue, P Jain - Journal of Cleaner Production, 2023 - Elsevier
Smart Cities can promote economic growth, sustainable transport, environmental
sustainability, and good governance among cities. These benefits can support cities in …