A multiagent federated reinforcement learning approach for plug-in electric vehicle fleet charging coordination in a residential community

Y Chu, Z Wei, X Fang, S Chen, Y Zhou - IEEE Access, 2022 - ieeexplore.ieee.org
The increasing penetration of distributed renewable energy and electric vehicles (EV) in
local microgrids/residential-community has brought a great challenge to balancing system …

Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks

J Qian, Y Jiang, X Liu, Q Wang, T Wang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
With the growing popularity of electric vehicles (EVs), maintaining power grid stability has
become a significant challenge. To address this issue, EV charging control strategies have …

Federated reinforcement learning for real-time electric vehicle charging and discharging control

Z Zhang, Y Jiang, Y Shi, Y Shi… - 2022 IEEE Globecom …, 2022 - ieeexplore.ieee.org
With the recent advances in mobile energy storage technologies, electric vehicles (EVs)
have become a crucial part of smart grids. When EVs participate in the demand response …

Dynamic pricing and energy management for profit maximization in multiple smart electric vehicle charging stations: A privacy-preserving deep reinforcement learning …

S Lee, DH Choi - Applied Energy, 2021 - Elsevier
Profit maximization of electric vehicle charging station (EVCS) operation yields an
increasing investment for the deployment of EVCSs, thereby increasing the penetration of …

A cooperative charging control strategy for electric vehicles based on multiagent deep reinforcement learning

L Yan, X Chen, Y Chen, J Wen - IEEE Transactions on Industrial …, 2022 - ieeexplore.ieee.org
The growth of electric vehicles (EVs) significantly increases the residential electricity
demand and potentially leads to the overload of the transformer in the distribution grid …

[HTML][HTML] Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles

S Hussain, RR Irshad, F Pallonetto, I Hussain… - Applied Energy, 2023 - Elsevier
The charging of electric vehicles (EVs) at residential premises is orchestrated through either
centralized or decentralized control mechanisms. The former emphasizes adherence to …

EV charging command fast allocation approach based on deep reinforcement learning with safety modules

J Zhang, Y Guan, L Che… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Efficient real-time management of electric vehicle (EV) charging in a charging station (CS) is
vital to the integration of large-scale EVs in power grids. It faces critical challenges such as …

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 …

Cooperative management for PV/ESS-enabled electric vehicle charging stations: A multiagent deep reinforcement learning approach

MJ Shin, DH Choi, J Kim - IEEE Transactions on Industrial …, 2019 - ieeexplore.ieee.org
This article proposes a novel multiagent deep reinforcement learning method for the energy
management of distributed electric vehicle charging stations with a solar photovoltaic system …

[HTML][HTML] Deep reinforcement learning for charging scheduling of electric vehicles considering distribution network voltage stability

D Liu, P Zeng, S Cui, C Song - Sensors, 2023 - mdpi.com
The rapid development of electric vehicle (EV) technology and the consequent charging
demand have brought challenges to the stable operation of distribution networks (DNs). The …