Feature extraction and classification of load dynamic characteristics based on lifting wavelet packet transform in power system load modeling-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Feature extraction and classification of load dynamic characteristics based on lifting wavelet packet transform in power system load modeling

Published:2014-11 Issue: Volume:62 Page:353-363
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:

Wang Zhenshu,Bian Shaorun,Lei Ming,Zhao Chuangang,Liu Yan,Zhao Zhifan

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference32 articles.

1. Digital power systems;Lu;Automat Electr Power Syst,2000

2. Study on essential principle and methods for load modeling;Tang;Power Syst Technol,2007

3. Load modeling based on support vector machine based on Bayesian evidence framework;Wang;Trans China Electrotech Soc,2009

4. Measurement-based load modeling using transfer functions for dynamic simulations;Visconti;IEEE Trans Power Syst,2014

5. Classification method for aggregated load dynamic characteristics;Lin;Automat Electr Power Syst,2005

Cited by 21 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. Human Multi-Activities Classification Using mmWave Radar: Feature Fusion in Time-Domain and PCANet;Sensors;2024-08-22

2. Feature extraction and classification of time-varying power load characteristics based on PCANet and CNN+Bi-LSTM algorithms;Electric Power Systems Research;2023-04

3. Classification for transient overvoltages in offshore wind farms based on multi-scale mathematical morphology;International Journal of Electrical Power & Energy Systems;2022-03

4. Artificial Intelligence Based Interpretable Uncertainty Forecasting Framework in the Configuration of a Virtual Power Plant Towards Carbon;SSRN Electronic Journal;2022

5. Rolling bearing fault diagnosis with combined convolutional neural networks and support vector machine;Measurement;2021-06

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