输电网规划框架

J. Teh, Yu-Huei Cheng, Ching-Ming Lai
{"title":"输电网规划框架","authors":"J. Teh, Yu-Huei Cheng, Ching-Ming Lai","doi":"10.1109/ICAWST.2017.8256450","DOIUrl":null,"url":null,"abstract":"As the penetration of wind power into the power system increases, the ability to assess the reliability impact of such interaction becomes more important. The composite reliability evaluations involving wind energy provide ample opportunities for assessing the benefits of different wind farm connection points. A connection to the weak area of the transmission network will require network reinforcement for absorbing the additional wind energy. Traditionally, the reinforcements are performed by constructing new transmission corridors. However, a new state-of-art technology such as the dynamic thermal rating (DTR) system, provides new reinforcement strategy and this requires new reliability assessment method. This paper demonstrates a methodology for assessing the cost and the reliability of a network reinforcement strategy by considering the DTR systems when large scale wind farms are connected to existing power network. Sequential Monte Carlo simulations were performed and all DTRs and wind speed were simulated using the auto-regressive moving average (ArMA) models.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A framework for transmission network planning\",\"authors\":\"J. Teh, Yu-Huei Cheng, Ching-Ming Lai\",\"doi\":\"10.1109/ICAWST.2017.8256450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the penetration of wind power into the power system increases, the ability to assess the reliability impact of such interaction becomes more important. The composite reliability evaluations involving wind energy provide ample opportunities for assessing the benefits of different wind farm connection points. A connection to the weak area of the transmission network will require network reinforcement for absorbing the additional wind energy. Traditionally, the reinforcements are performed by constructing new transmission corridors. However, a new state-of-art technology such as the dynamic thermal rating (DTR) system, provides new reinforcement strategy and this requires new reliability assessment method. This paper demonstrates a methodology for assessing the cost and the reliability of a network reinforcement strategy by considering the DTR systems when large scale wind farms are connected to existing power network. Sequential Monte Carlo simulations were performed and all DTRs and wind speed were simulated using the auto-regressive moving average (ArMA) models.\",\"PeriodicalId\":378618,\"journal\":{\"name\":\"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAWST.2017.8256450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2017.8256450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着风电对电力系统渗透的增加,评估这种相互作用对可靠性影响的能力变得更加重要。涉及风能的综合可靠性评估为评估不同风电场连接点的效益提供了充分的机会。连接到输电网络的薄弱区域将需要网络加固以吸收额外的风能。传统上,加固是通过建造新的输电走廊来实现的。然而,动态热评级(DTR)系统等最新技术提供了新的加固策略,这就需要新的可靠性评估方法。本文通过考虑大型风电场与现有电网连接时的DTR系统,展示了一种评估网络加固策略成本和可靠性的方法。采用自回归移动平均(ArMA)模型进行时序蒙特卡罗模拟,并模拟所有dtr和风速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A framework for transmission network planning
As the penetration of wind power into the power system increases, the ability to assess the reliability impact of such interaction becomes more important. The composite reliability evaluations involving wind energy provide ample opportunities for assessing the benefits of different wind farm connection points. A connection to the weak area of the transmission network will require network reinforcement for absorbing the additional wind energy. Traditionally, the reinforcements are performed by constructing new transmission corridors. However, a new state-of-art technology such as the dynamic thermal rating (DTR) system, provides new reinforcement strategy and this requires new reliability assessment method. This paper demonstrates a methodology for assessing the cost and the reliability of a network reinforcement strategy by considering the DTR systems when large scale wind farms are connected to existing power network. Sequential Monte Carlo simulations were performed and all DTRs and wind speed were simulated using the auto-regressive moving average (ArMA) models.
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
期刊最新文献
Deep convolutional neural network classifier for travel patterns using binary sensors Establishing the application of personal healthcare service system for cancer patients Disaster state information management gis system based on tiled diplay environment Keynote speech I: Big data, non-big data, and algorithms for recognizing the real world data Improving the performance of lossless reversible steganography via data sharing
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1