Privacy-preserving context-based electric vehicle dispatching for energy scheduling in microgrids: An online learning approach

Y Liu, P Zhou, L Yang, Y Wu, Z Xu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Electric Vehicles (EVs) are beginning to play a key role in the fast developing area of
Internet of Things (IoT). Numerous results have shown the feasibility of vehicle-to-building …

Context Aware-Resource Optimality in Electric Vehicle Smart2Charge Application. A Deep Reinforcement Learning Base Approach

M Sharif, G Lückemeyer, H Seker - IEEE Access, 2023 - ieeexplore.ieee.org
Electric vehicle (EV) adoption is expanding, posing new issues for grid operators, fleet
operators, charging station operators, and EV owners. The challenge is to devise an efficient …

Multilevel deep reinforcement learning for secure reservation-based electric vehicle charging via differential privacy and energy storage system

S Lee, DH Choi - IEEE Transactions on Vehicular Technology, 2024 - ieeexplore.ieee.org
This paper presents a multilevel deep reinforcement learning (DRL) algorithm for a privacy-
preserving charging of reserved individual electric vehicles (EVs) and the secure operation …

Energy management for regional microgrids considering energy transmission of electric vehicles between microgrids

F Jiao, Y Zou, Y Zhou, Y Zhang, X Zhang - Energy, 2023 - Elsevier
As the proliferation of electric vehicles (EVs) continues to accelerate, the inherent attributes
of EVs warrant meticulous consideration in the realm of energy dispatch. In order to evaluate …

Smart EV Charging with Context-Awareness: Enhancing Resource Utilization via Deep Reinforcement Learning

M Sharif, H Seker - IEEE Access, 2024 - ieeexplore.ieee.org
The widespread adoption of electric vehicles (EVs) has introduced new challenges for
stakeholders ranging from grid operators to EV owners. A critical challenge is to develop an …

Modeling Practically Private Wireless Vehicle to Grid System With Federated Reinforcement Learning

SR Pokhrel, MB Hossain, A Walid - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The Smart Grid (SG) infrastructure plan offers growth opportunities for the electric vehicle
(EV) industry and aims to reduce dependence on fossil fuels. Surprisingly, the literature …

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 …

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 …

Deep Q-Learning-Based Smart Scheduling of EVs for Demand Response in Smart Grids

VR Chifu, T Cioara, CB Pop, HG Rusu, I Anghel - Applied Sciences, 2024 - mdpi.com
Economic and policy factors are driving the continuous increase in the adoption and usage
of electrical vehicles (EVs). However, despite being a cleaner alternative to combustion …

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 …