Multi-agent reinforcement learning for intelligent V2G integration in future transportation systems
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 …
They are environmentally friendly and can also be integrated as distributed energy …
A multi-agent deep reinforcement learning paradigm to improve the robustness and resilience of grid connected electric vehicle charging stations against the …
R Sepehrzad, A Khodadadi, S Adinehpour, M Karimi - Energy, 2024 - Elsevier
The rising deployment of electric vehicle charging stations (EVCS) in existing power grids
and their integration with electric vehicles through communication systems are increasingly …
and their integration with electric vehicles through communication systems are increasingly …
[HTML][HTML] Leveraging machine learning for efficient EV integration as mobile battery energy storage systems: Exploring strategic frameworks and incentives
MJ Salehpour, MJ Hossain - Journal of Energy Storage, 2024 - Elsevier
The emergence of electric vehicles is reshaping the energy landscape, requiring the
development of innovative energy integration mechanisms to engage prosumers. However …
development of innovative energy integration mechanisms to engage prosumers. However …
Multiagent deep reinforcement learning for electric vehicle fast charging station pricing game in electricity-transportation nexus
Transportation electrification, involving large-scale integration of electric vehicles (EV) and
fast charging stations (FCS), constitutes one of the key enablers toward decarbonization …
fast charging stations (FCS), constitutes one of the key enablers toward decarbonization …
When hierarchical federated learning meets stochastic game: toward an intelligent UAV charging in urban prosumers
Unmanned aerial vehicles (UAVs) nowadays are developing rapidly for various applications
such as UAV taxis and delivery drones. However, the limited battery energy restricts the …
such as UAV taxis and delivery drones. However, the limited battery energy restricts the …
Aggregator pricing and electric vehicles charging strategy based on a two-layer deep learning model
H Lin, Y Zhou, Y Li, H Zheng - Electric Power Systems Research, 2024 - Elsevier
In response to the increasing number of EVs (electric vehicles) being charged in a disorderly
manner, this paper proposes a two-layer deep learning model based on aggregator pricing …
manner, this paper proposes a two-layer deep learning model based on aggregator pricing …
Peer-to-peer energy transactions for prosumers based on improved deep deterministic policy gradient algorithm
With the evolution of the power market, the active involvement of prosumers in both
consuming renewable energy and maximizing financial gains has emerged as a pivotal and …
consuming renewable energy and maximizing financial gains has emerged as a pivotal and …
A market-based real-time algorithm for congestion alleviation incorporating EV demand response in active distribution networks
M Menghwar, J Yan, Y Chi, MA Amin, Y Liu - Applied Energy, 2024 - Elsevier
The dynamic charging behavior of electric vehicles (EVs) is causing frequent line-
overloading problems and serious power security issues. Controlled and smart charging …
overloading problems and serious power security issues. Controlled and smart charging …
Dynamic many-to-many task offloading in vehicular fog computing: A multi-agent drl approach
Confronted with the increasing computation-intensive requirements of vehicular
applications, vehicular fog computing (VFC) has emerged as the promising solution to …
applications, vehicular fog computing (VFC) has emerged as the promising solution to …
Deep reinforcement learning-based charging price determination considering the coordinated operation of hydrogen fuel cell electric vehicle, power network and …
B Li, J Li, M Han - IEEE Access, 2023 - ieeexplore.ieee.org
Currently, hydrogen fuel cell electric vehicles (HFCEVs) are becoming more financially
accessible as an alternative to petroleum-powered vehicles, while also decreasing carbon …
accessible as an alternative to petroleum-powered vehicles, while also decreasing carbon …