Methodology for Forming a Training Sample for Power Systems Emergency Control Algorithm Based on Machine Learning
Author:
Affiliation:
1. Ural Federal University,Department of Automated Electrical Systems,Yekaterinburg,Russia
2. Tajik Technical University,Department of Electric Stations,Tajikistan,Dushanbe
Funder
Russian Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10296113/10296212/10296257.pdf?arnumber=10296257
Reference22 articles.
1. A Unified Online Deep Learning Prediction Model for Small Signal and Transient Stability
2. Time Series-Analysis Based Engineering of High-Dimensional Wide-Area Stability Indices for Machine Learning
3. Novel and efficient randomized algorithms for feature selection
4. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
5. Solution of the emergency control of synchronous generator modes based on the local measurements to ensure the dynamic stability
Cited by 1 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. Methodology for Transient Stability Enhancement of Power Systems Based on Machine Learning Algorithms and Fast Valving in a Steam Turbine;Mathematics;2024-05-24
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