A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges

O Sadeghian, A Oshnoei, B Mohammadi-Ivatloo… - Journal of Energy …, 2022 - Elsevier
The role of electric vehicles (EVs) in energy systems will be crucial over the upcoming years
due to their environmental-friendly nature and ability to mitigate/absorb excess power from …

A hybrid method for power demand prediction of electric vehicles based on SARIMA and deep learning with integration of periodic features

F Ren, C Tian, G Zhang, C Li, Y Zhai - Energy, 2022 - Elsevier
Accurate power demand prediction of electrical vehicles (EVs) is crucial to power grid
operation. To fully utilize the existing knowledge of EVs' power demand and further improve …

Using bayesian deep learning for electric vehicle charging station load forecasting

D Zhou, Z Guo, Y Xie, Y Hu, D Jiang, Y Feng, D Liu - Energies, 2022 - mdpi.com
In recent years, replacing internal combustion engine vehicles with electric vehicles has
been a significant option for supporting reducing carbon emissions because of fossil fuel …

Deep learning LSTM recurrent neural network model for prediction of electric vehicle charging demand

J Shanmuganathan, AA Victoire, G Balraj, A Victoire - Sustainability, 2022 - mdpi.com
The immense growth and penetration of electric vehicles has become a major component of
smart transport systems; thereby decreasing the greenhouse gas emissions that pollute the …

Energy demand load forecasting for electric vehicle charging stations network based on convlstm and biconvlstm architectures

F Mohammad, DK Kang, MA Ahmed, YC Kim - IEEE Access, 2023 - ieeexplore.ieee.org
The electrification of transport has proved to be a breakthrough to uplift the sustainable and
eco-friendly platform in the global sector in which electric vehicles (EVs) are considered …

Day-ahead forecast of electric vehicle charging demand with deep neural networks

G Van Kriekinge, C De Cauwer… - World Electric Vehicle …, 2021 - mdpi.com
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 …

[HTML][HTML] A data-driven framework for medium-term electric vehicle charging demand forecasting

A Orzechowski, L Lugosch, H Shu, R Yang, W Li… - Energy and AI, 2023 - Elsevier
The rapid phase-in of electric vehicles (EV) will cause unprecedented issues with managing
the supply of electricity and charging stations. It is in the interest of utility providers and …

Electric vehicles load forecasting for day-ahead market participation using machine and deep learning methods

ZN Bampos, VM Laitsos, KD Afentoulis, SI Vagropoulos… - Applied Energy, 2024 - Elsevier
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 …

Self-supervised online learning algorithm for electric vehicle charging station demand and event prediction

MA Zamee, D Han, H Cha, D Won - Journal of Energy Storage, 2023 - Elsevier
With the increasing popularity of electric vehicles (EVs), countries are setting up new
charging stations to meet up the rising demand. Therefore, accurately forecasting charging …

Metaprobformer for charging load probabilistic forecasting of electric vehicle charging stations

X Huang, D Wu, B Boulet - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
The penetration of electric vehicles (EV) has been increasing rapidly in recent years. Electric
vehicle charging load poses a huge demand on the power grids. The forecasting for electric …