A novel series arc fault detection method for photovoltaic system based on multi-input neural network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A novel series arc fault detection method for photovoltaic system based on multi-input neural network

Published:2022-09 Issue: Volume:140 Page:108018
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Chen Xiaoqi,Gao Wei,Hong Cui,Tu Yanzhao

Funder

Natural Science Foundation of Jiangxi Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference32 articles.

1. REN21. Renewables 2020 global status report. Renewable energy policy network for the 21st century. Paris: REN21 2020.

2. Arc fault detection and localization in photovoltaic systems using feature distribution maps of parallel capacitor currents;Xiong;IEEE J Photovoltaics,2018

3. National Electrical Code, Article 690—Solar Photovoltaic Systems 2011.

4. Series arc fault detection in photovoltaic systems based on signal-to-noise ratio characteristics using cross-correlation function;Ahmadi;IEEE Trans Ind Inf,2020

5. The detection of series arc fault in photovoltaic systems based on the arc current entropy;Georgijevic;IEEE Trans Power Electron,2016

Cited by 28 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. Prognostics and health management of photovoltaic systems based on deep learning: A state-of-the-art review and future perspectives;Renewable and Sustainable Energy Reviews;2024-11

2. Fault diagnosis of photovoltaic array with multi-module fusion under hyperparameter optimization;Energy Conversion and Management;2024-11

3. Arc-1DCNN: An enhanced model for series arc fault detection;Measurement;2024-07

4. Integration of wavelet packet transform, residual convolution neural network, and support vector machine for series arc fault detection;AIP Advances;2024-06-01

5. Real-time operation risk monitoring method for power grid based on cloud edge collaboration technology;Journal of Physics: Conference Series;2024-06-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3