风电高渗透配电系统电能质量评价

N. K. Swarnkar, Om Prakash Mahela, M. Lalwani
{"title":"风电高渗透配电系统电能质量评价","authors":"N. K. Swarnkar, Om Prakash Mahela, M. Lalwani","doi":"10.1109/i-PACT52855.2021.9696822","DOIUrl":null,"url":null,"abstract":"In this paper, evaluation of power quality (PQ) disturbances observed with a distribution system with availability of high penetration of wind power generation is achieved using the hybrid algorithm designed applying the Hilbert transform (HT) and Stockwell transform (ST). An index for PQ identification (IPI) and an index for event location (IPL) have been designed by processing the voltage signals using the ST and HT. IPI index effectively recognize PQ issues associated with utility grid with availability of high wind energy penetration. This is achieved for the grid operations such as switching of the loads & capacitors, feeder operations, wind power plant operations and island formation in the presence of high wind power generation. These events have been categorized using the decision rules driven by the features computed from the IPI and IPL indices. Proposed method performs better relative to Discrete Wavelet transform (DWT) based technique. Results are validated in MATLAB using an IEEE-13 node test network interfaced with wind power plants.","PeriodicalId":335956,"journal":{"name":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evaluation of Power Quality in Distribution System with High Penetration of Wind Power Generation\",\"authors\":\"N. K. Swarnkar, Om Prakash Mahela, M. Lalwani\",\"doi\":\"10.1109/i-PACT52855.2021.9696822\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, evaluation of power quality (PQ) disturbances observed with a distribution system with availability of high penetration of wind power generation is achieved using the hybrid algorithm designed applying the Hilbert transform (HT) and Stockwell transform (ST). An index for PQ identification (IPI) and an index for event location (IPL) have been designed by processing the voltage signals using the ST and HT. IPI index effectively recognize PQ issues associated with utility grid with availability of high wind energy penetration. This is achieved for the grid operations such as switching of the loads & capacitors, feeder operations, wind power plant operations and island formation in the presence of high wind power generation. These events have been categorized using the decision rules driven by the features computed from the IPI and IPL indices. Proposed method performs better relative to Discrete Wavelet transform (DWT) based technique. Results are validated in MATLAB using an IEEE-13 node test network interfaced with wind power plants.\",\"PeriodicalId\":335956,\"journal\":{\"name\":\"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/i-PACT52855.2021.9696822\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Innovations in Power and Advanced Computing Technologies (i-PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i-PACT52855.2021.9696822","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文利用希尔伯特变换(HT)和斯托克韦尔变换(ST)设计的混合算法,对具有风电高渗透可用性的配电系统的电能质量(PQ)扰动进行了评估。通过对电压信号进行ST和HT处理,设计了PQ识别指标(IPI)和事件定位指标(IPL)。IPI指数有效地识别了与高风能渗透率的公用事业电网相关的PQ问题。这是在电网运行中实现的,如负载和电容器的切换、馈线运行、风力发电厂运行和在高风力发电的情况下形成岛屿。使用由IPI和IPL指数计算的特征驱动的决策规则对这些事件进行分类。该方法相对于基于离散小波变换(DWT)的方法具有更好的性能。通过与风电场对接的IEEE-13节点测试网络,在MATLAB中对结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Power Quality in Distribution System with High Penetration of Wind Power Generation
In this paper, evaluation of power quality (PQ) disturbances observed with a distribution system with availability of high penetration of wind power generation is achieved using the hybrid algorithm designed applying the Hilbert transform (HT) and Stockwell transform (ST). An index for PQ identification (IPI) and an index for event location (IPL) have been designed by processing the voltage signals using the ST and HT. IPI index effectively recognize PQ issues associated with utility grid with availability of high wind energy penetration. This is achieved for the grid operations such as switching of the loads & capacitors, feeder operations, wind power plant operations and island formation in the presence of high wind power generation. These events have been categorized using the decision rules driven by the features computed from the IPI and IPL indices. Proposed method performs better relative to Discrete Wavelet transform (DWT) based technique. Results are validated in MATLAB using an IEEE-13 node test network interfaced with wind power plants.
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