A review of optimal charging strategy for electric vehicles under dynamic pricing schemes in the distribution charging network

A Amin, WUK Tareen, M Usman, H Ali, I Bari, B Horan… - Sustainability, 2020 - mdpi.com
This study summarizes a critical review on EVs' optimal charging and scheduling under
dynamic pricing schemes. A detailed comparison of these schemes, namely, Real Time …

A review on energy efficient technologies for electric vehicle applications

RT Yadlapalli, A Kotapati, R Kandipati… - Journal of Energy …, 2022 - Elsevier
This paper presents the technological advancements of the electric vehicles (EVs) all over
the world. The first emphasis is on the various types of the EVs along with the energy …

Data-driven charging demand prediction at public charging stations using supervised machine learning regression methods

A Almaghrebi, F Aljuheshi, M Rafaie, K James… - Energies, 2020 - mdpi.com
Plug-in Electric Vehicle (PEV) user charging behavior has a significant influence on a
distribution network and its reliability. Generally, monitoring energy consumption has …

Electric vehicle scheduling: State of the art, critical challenges, and future research opportunities

J Pasha, B Li, Z Elmi, AM Fathollahi-Fard, Y Lau… - Journal of Industrial …, 2024 - Elsevier
Electric vehicles can be perceived as a means to achieve carbon reduction, energy
efficiency, and sustainable development of the transportation industry. Electric vehicle sales …

The development of a techno-economic model for assessment of cost of energy storage for vehicle-to-grid applications in a cold climate

MM Rahman, E Gemechu, AO Oni, A Kumar - Energy, 2023 - Elsevier
With the growing number of electric vehicles in the transportation sector aimed at reducing
greenhouse gas emissions, vehicle-to-grid (V2G) technology can play an important role in …

[HTML][HTML] Predictive control and coordination for energy community flexibility with electric vehicles, heat pumps and thermal energy storage

C Srithapon, D Månsson - Applied Energy, 2023 - Elsevier
Electrification of private transportation and residential heating is a potential action to
decrease significantly carbon emissions. However, the lack of coordination of such …

A deep learning approach for prediction of electrical vehicle charging stations power demand in regulated electricity markets: The case of Morocco

M Boulakhbar, M Farag, K Benabdelaziz… - Cleaner Energy …, 2022 - Elsevier
The transport sector is a prominent source of increasing fuel consumption and greenhouse
gas (GHG) emissions. Electric vehicle (EV) is deemed an appealing solution for those …

A novel multi-objective optimization based multi-agent deep reinforcement learning approach for microgrid resources planning

MS Abid, HJ Apon, S Hossain, A Ahmed, R Ahshan… - Applied Energy, 2024 - Elsevier
Multi-agent deep reinforcement learning (MADRL) approaches are at the forefront of
contemporary research in optimum electric vehicle (EV) charging scheduling challenges …

A review on mathematical models of electric vehicle for energy management and grid integration studies

P Thomas, PK Shanmugam - Journal of Energy Storage, 2022 - Elsevier
Electric Vehicle (EV) users are always concerned about the vehicle's mileage, available
electric range, availability of the nearest charging station, power processing capabilities, slot …

Mitigating transformer loss of life and reducing the hazard of failure by the smart EV charging

M Soleimani, M Kezunovic - IEEE Transactions on Industry …, 2020 - ieeexplore.ieee.org
The impact of uncoordinated charging of electrical vehicles (EVs) under high penetration on
distribution transformers is studied. It was shown that EV charging may cause prolonged …