基于人工神经网络的电力系统稳定器

J. Kumar, P. P. Kumar, Aeidapu Mahesh, Ankit Shrivastava
{"title":"基于人工神经网络的电力系统稳定器","authors":"J. Kumar, P. P. Kumar, Aeidapu Mahesh, Ankit Shrivastava","doi":"10.1109/ICPES.2011.6156656","DOIUrl":null,"url":null,"abstract":"This paper describes a systematic approach for designing a self-tuning adaptive power system stabilizer (PSS) based on artificial neural network (ANN). An ANN is used for self-tuning the parameters of PSS e.g. stabilizing gain Kstab and time constant (T1) for Lead PSS in realtime. The inputs to the ANN are generator terminal active power (P) and reactive power (Q). Investigations are carried out to assess the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) over a wide range of loading conditions. The simulations are performed using Matlab/Simulink's neural network toolbox. The simulation and experimental results demonstrate the effective dynamic performance of the proposed system.","PeriodicalId":158903,"journal":{"name":"2011 International Conference on Power and Energy Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Power system stabilizer based on artificial neural network\",\"authors\":\"J. Kumar, P. P. Kumar, Aeidapu Mahesh, Ankit Shrivastava\",\"doi\":\"10.1109/ICPES.2011.6156656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a systematic approach for designing a self-tuning adaptive power system stabilizer (PSS) based on artificial neural network (ANN). An ANN is used for self-tuning the parameters of PSS e.g. stabilizing gain Kstab and time constant (T1) for Lead PSS in realtime. The inputs to the ANN are generator terminal active power (P) and reactive power (Q). Investigations are carried out to assess the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) over a wide range of loading conditions. The simulations are performed using Matlab/Simulink's neural network toolbox. The simulation and experimental results demonstrate the effective dynamic performance of the proposed system.\",\"PeriodicalId\":158903,\"journal\":{\"name\":\"2011 International Conference on Power and Energy Systems\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Power and Energy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPES.2011.6156656\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Power and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPES.2011.6156656","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

介绍了一种基于人工神经网络(ANN)的电力系统自整定自适应稳定器的系统设计方法。利用人工神经网络对PSS的参数进行自整定,实时稳定前置PSS的增益Kstab和时间常数T1。人工神经网络的输入为发电机终端有功功率(P)和无功功率(Q)。研究了基于人工神经网络的自调谐PSS (ST-ANNPSS)系统在各种负载条件下的动态性能。利用Matlab/Simulink的神经网络工具箱进行仿真。仿真和实验结果表明,该系统具有良好的动态性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power system stabilizer based on artificial neural network
This paper describes a systematic approach for designing a self-tuning adaptive power system stabilizer (PSS) based on artificial neural network (ANN). An ANN is used for self-tuning the parameters of PSS e.g. stabilizing gain Kstab and time constant (T1) for Lead PSS in realtime. The inputs to the ANN are generator terminal active power (P) and reactive power (Q). Investigations are carried out to assess the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) over a wide range of loading conditions. The simulations are performed using Matlab/Simulink's neural network toolbox. The simulation and experimental results demonstrate the effective dynamic performance of the proposed system.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信