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[HTML][HTML] Applications of reinforcement learning in energy systems
Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …
renewable energy technologies and improve efficiencies, leading to the integration of many …
Reinforcement learning based EV charging management systems–a review
To mitigate global warming and energy shortage, integration of renewable energy
generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been …
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
This paper investigates the electric vehicle (EV) charging scheduling problem for public EV
charging stations (EVCSs) that can accommodate heterogeneous charging demands …
charging stations (EVCSs) that can accommodate heterogeneous charging demands …
Effective charging planning based on deep reinforcement learning for electric vehicles
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 …
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 …
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
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 …
[HTML][HTML] Leveraging machine learning for efficient EV integration as mobile battery energy storage systems: Exploring strategic frameworks and incentives
The emergence of electric vehicles is resha** 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 …
Ensemble learning for charging load forecasting of electric vehicle charging stations
Electric vehicles (EVs) can help reduce the dependency on fossil oil and increasing
concerns on environmental pollution problems. However, due to the complex charging …
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
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 …
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
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 …
smart management when charging electric vehicles (EVs) is becoming more and more …