Model-free real-time EV charging scheduling based on deep reinforcement learning
Driven by the recent advances in electric vehicle (EV) technologies, EVs have become
important for smart grid economy. When EVs participate in demand response program which …
important for smart grid economy. When EVs participate in demand response program which …
Constrained EV charging scheduling based on safe deep reinforcement learning
Electric vehicles (EVs) have been popularly adopted and deployed over the past few years
because they are environment-friendly. When integrated into smart grids, EVs can operate …
because they are environment-friendly. When integrated into smart grids, EVs can operate …
Electric vehicle charging management based on deep reinforcement learning
A time-variable time-of-use electricity price can be used to reduce the charging costs for
electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the …
electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the …
Deep reinforcement learning for continuous electric vehicles charging control with dynamic user behaviors
This paper aims to crack the individual EV charging scheduling problem considering the
dynamic user behaviors and the electricity price. The uncertainty of the EV charging demand …
dynamic user behaviors and the electricity price. The uncertainty of the EV charging demand …
Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid
K Park, I Moon - Applied energy, 2022 - Elsevier
As the competitive advantages of electric vehicles, both in terms of operating costs and eco-
friendly characteristics have gained attention, the demand for electric vehicles has …
friendly characteristics have gained attention, the demand for electric vehicles has …
Multistep multiagent reinforcement learning for optimal energy schedule strategy of charging stations in smart grid
An efficient energy scheduling strategy of a charging station is crucial for stabilizing the
electricity market and accommodating the charging demand of electric vehicles (EVs). Most …
electricity market and accommodating the charging demand of electric vehicles (EVs). Most …
Electric vehicle charging and discharging algorithm based on reinforcement learning with data-driven approach in dynamic pricing scheme
In the smart grid environment, the penetration of electric vehicle (EV) is increasing, and
dynamic pricing and vehicle-to-grid technologies are being introduced. Consequently …
dynamic pricing and vehicle-to-grid technologies are being introduced. Consequently …
Reinforcement learning of heuristic EV fleet charging in a day-ahead electricity market
This paper addresses the problem of defining a day-ahead consumption plan for charging a
fleet of electric vehicles (EVs), and following this plan during operation. A challenge herein …
fleet of electric vehicles (EVs), and following this plan during operation. A challenge herein …
A transfer learning method for electric vehicles charging strategy based on deep reinforcement learning
K Wang, H Wang, Z Yang, J Feng, Y Li, J Yang, Z Chen - Applied Energy, 2023 - Elsevier
Reinforcement learning (RL) is popularly used for the development of an orderly charging
strategy for electric vehicles (EVs). However, a new environment (eg, charging areas and …
strategy for electric vehicles (EVs). However, a new environment (eg, charging areas and …
Probabilistic charging power forecast of EVCS: Reinforcement learning assisted deep learning approach
The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely
deployed with the development of large-scale transportation electrifications. However, since …
deployed with the development of large-scale transportation electrifications. However, since …