Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks-Reference-Cited by-同舟云学术

Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks

Published:2024-02-01 Issue:3 Volume:11 Page:5511-5525
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Qian Junkai¹,Jiang Yuning²^ORCID,Liu Xin³^ORCID,Wang Qiong⁴,Wang Ting¹^ORCID,Shi Yuanming³^ORCID,Chen Wei⁵^ORCID

Affiliation:

1. MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application and the Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China

2. Automatic Control Laboratory, EPFL, Lausanne, Switzerland

3. School of Information Science and Technology, ShanghaiTech University, Shanghai, China

4. State Grid Beijing Electric Power Company, Beijing, China

5. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

Natural Science Foundation of Shanghai

Shanghai Sailing Program

Open Research Fund of Engineering Research Center of Software/Hardware Co-Design Technology and Application, Ministry of Education

Shenzhen Science and Technology Plan Project

Swiss National Science Foundation under the NCCR Automation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10413935/10225344.pdf?arnumber=10225344

Reference57 articles.

1. Comparison of Climate Change Impact Between Power System of Electric Vehicles and Internal Combustion Engine Vehicles

2. A Comprehensive review on electric vehicles charging infrastructures and their impacts on power-quality of the utility grid

3. Review of Positive and Negative Impacts of Electric Vehicles Charging on Electric Power Systems

4. Data-Driven Coordinated Charging for Electric Vehicles with Continuous Charging Rates: A Deep Policy Gradient Approach

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimization of multi-vehicle charging and discharging efficiency under time constraints based on reinforcement learning;Alexandria Engineering Journal;2024-10

2. Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation;Batteries;2023-12-15