Integrating electric vehicles as virtual power plants: A comprehensive review on vehicle-to-grid (V2G) concepts, interface topologies, marketing and future prospects

M İnci, MM Savrun, Ö Çelik - Journal of Energy Storage, 2022 - Elsevier
Global factors such as energy consumption and environmental issues encourage the
utilization of electric vehicles (EVs) as alternative energy sources besides transportation …

[HTML][HTML] Applications of reinforcement learning in energy systems

ATD Perera, P Kamalaruban - Renewable and Sustainable Energy …, 2021 - Elsevier
Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

Reinforcement learning for demand response: A review of algorithms and modeling techniques

JR Vázquez-Canteli, Z Nagy - Applied energy, 2019 - Elsevier
Buildings account for about 40% of the global energy consumption. Renewable energy
resources are one possibility to mitigate the dependence of residential buildings on the …

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 …

[HTML][HTML] Vehicle-to-X (V2X) implementation: An overview of predominate trial configurations and technical, social and regulatory challenges

C Gschwendtner, SR Sinsel, A Stephan - Renewable and Sustainable …, 2021 - Elsevier
The uptake of electric vehicles supports decarbonization and increasingly interconnects the
electricity and transport system. While the integration of electric vehicles could challenge …

Electric vehicles charging infrastructure demand and deployment: challenges and solutions

PP Singh, F Wen, I Palu, S Sachan, S Deb - Energies, 2022 - mdpi.com
Present trends indicate that electrical vehicles (EVs) are favourable technology for road
network transportation. The lack of easily accessible charging stations will be a negative …

Strategies for controlling microgrid networks with energy storage systems: A review

M Al-Saadi, M Al-Greer, M Short - Energies, 2021 - mdpi.com
Distributed Energy Storage Systems are considered key enablers in the transition from the
traditional centralized power system to a smarter, autonomous, and decentralized system …

Multi-agent reinforcement learning for intelligent V2G integration in future transportation systems

J Dong, A Yassine, A Armitage… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Electric vehicles (EVs) are the backbone of the future intelligent transportation system (ITS).
They are environmentally friendly and can also be integrated as distributed energy …

[HTML][HTML] Optimal vehicle-to-grid control for supplementary frequency regulation using deep reinforcement learning

F Alfaverh, M Denaï, Y Sun - Electric Power Systems Research, 2023 - Elsevier
Abstract The expanding Electric Vehicle (EV) market presents a new opportunity for electric
vehicles to deliver a wide range of valuable grid services. Indeed, the emerging Vehicle-to …

A robust vehicle to grid aggregation framework for electric vehicles charging cost minimization and for smart grid regulation

U ur Rehman - International Journal of Electrical Power & Energy …, 2022 - Elsevier
In this paper, we propose an optimal hierarchical bi-directional aggregation algorithm for the
electric vehicles (EVs) integration in the smart grid (SG) using Vehicle to Grid (V2G) …