[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 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 …

A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile

Z Zhao, CKM Lee, J Ren - Applied energy, 2024 - Elsevier
This paper investigates the electric vehicle (EV) charging scheduling problem for public EV
charging stations (EVCSs) that can accommodate heterogeneous charging demands …

Effective charging planning based on deep reinforcement learning for electric vehicles

C Zhang, Y Liu, F Wu, B Tang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Electric vehicles (EVs) are viewed as an attractive option to reduce carbon emission and fuel
consumption, but the popularization of EVs has been hindered by the cruising range …

[HTML][HTML] Electric vehicle charging scheduling control strategy for the large-scale scenario with non-cooperative game-based multi-agent reinforcement learning

L Fu, T Wang, M Song, Y Zhou, S Gao - International Journal of Electrical …, 2023 - Elsevier
With the popularity of electric vehicles (EVs), electric vehicle charging scheduling control in
the complex urban environment has become a hot research issue, especially the use of …

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] 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 resha** the energy landscape, requiring the
development of innovative energy integration mechanisms to engage prosumers. However …

Ensemble learning for charging load forecasting of electric vehicle charging stations

X Huang, D Wu, B Boulet - 2020 IEEE Electric Power and …, 2020 - ieeexplore.ieee.org
Electric vehicles (EVs) can help reduce the dependency on fossil oil and increasing
concerns on environmental pollution problems. However, due to the complex charging …

[HTML][HTML] Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation

MM Shibl, LS Ismail, AM Massoud - Energy Reports, 2023 - Elsevier
EVs are becoming more popular and widely used worldwide due to their environmentally
friendliness as part of the world efforts to decrease the effects of climate change. Moreover …

[HTML][HTML] Power output optimization of electric vehicles smart charging hubs using deep reinforcement learning

A Bertolini, MSE Martins, SM Vieira… - Expert Systems with …, 2022 - Elsevier
Since most branches of the distribution grid may already be close to their maximum capacity,
smart management when charging electric vehicles (EVs) is becoming more and more …