哈萨克斯坦电力系统架空输电线路停电数据分析

Yerzhigit Bapin, S. Ekisheva, M. Papic, Vasilios Zarikas
{"title":"哈萨克斯坦电力系统架空输电线路停电数据分析","authors":"Yerzhigit Bapin, S. Ekisheva, M. Papic, Vasilios Zarikas","doi":"10.1109/PMAPS47429.2020.9183569","DOIUrl":null,"url":null,"abstract":"This paper presents a first comprehensive statistical study of transmission inventory and outage data of overhead AC circuits in the Kazakhstan Electricity Grid Operating Company (KEGOC). The analysis is based on the data collected and reported to the KEGOC centralized outage data collection system during the years 2013 to 2018. The outage-data statistics of KEGOC have been analyzed to demonstrate the leading cause-code and seasonal contributions to the automatic outages of overhead transmission lines of 200 kV and above voltage classes. The KEGOC’s 6-year collected outage data are used to estimate basic reliability indices (frequency of automatic and sustained automatic outages per circuit and per hundred kilometers, outage duration, and an element unavailability) that are needed to perform any type of probabilistic reliability studies. Also, these 6-year collected outage data are used to assess and benchmark the reliability performance of a system’s zones. The importance of these kinds of data and analysis for reliability applications is stressed.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Outage Data Analysis of the Overhead Transmission Lines in Kazakhstan Power System\",\"authors\":\"Yerzhigit Bapin, S. Ekisheva, M. Papic, Vasilios Zarikas\",\"doi\":\"10.1109/PMAPS47429.2020.9183569\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a first comprehensive statistical study of transmission inventory and outage data of overhead AC circuits in the Kazakhstan Electricity Grid Operating Company (KEGOC). The analysis is based on the data collected and reported to the KEGOC centralized outage data collection system during the years 2013 to 2018. The outage-data statistics of KEGOC have been analyzed to demonstrate the leading cause-code and seasonal contributions to the automatic outages of overhead transmission lines of 200 kV and above voltage classes. The KEGOC’s 6-year collected outage data are used to estimate basic reliability indices (frequency of automatic and sustained automatic outages per circuit and per hundred kilometers, outage duration, and an element unavailability) that are needed to perform any type of probabilistic reliability studies. Also, these 6-year collected outage data are used to assess and benchmark the reliability performance of a system’s zones. The importance of these kinds of data and analysis for reliability applications is stressed.\",\"PeriodicalId\":126918,\"journal\":{\"name\":\"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PMAPS47429.2020.9183569\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMAPS47429.2020.9183569","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

本文首次对哈萨克斯坦电网运营公司(KEGOC)架空交流线路的输电库存和停电数据进行了全面的统计研究。该分析基于2013年至2018年期间收集并报告给KEGOC集中停电数据收集系统的数据。通过对KEGOC的停电数据统计分析,揭示了200千伏及以上电压等级架空输电线路自动停电的主要原因代码和季节性贡献。KEGOC收集的6年停电数据用于估计执行任何类型的概率可靠性研究所需的基本可靠性指标(每条线路和每百公里自动和持续自动停电的频率、停电持续时间和元件不可用性)。此外,这些6年收集的停机数据用于评估系统区域的可靠性性能并对其进行基准测试。强调了这类数据和分析对可靠性应用的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Outage Data Analysis of the Overhead Transmission Lines in Kazakhstan Power System
This paper presents a first comprehensive statistical study of transmission inventory and outage data of overhead AC circuits in the Kazakhstan Electricity Grid Operating Company (KEGOC). The analysis is based on the data collected and reported to the KEGOC centralized outage data collection system during the years 2013 to 2018. The outage-data statistics of KEGOC have been analyzed to demonstrate the leading cause-code and seasonal contributions to the automatic outages of overhead transmission lines of 200 kV and above voltage classes. The KEGOC’s 6-year collected outage data are used to estimate basic reliability indices (frequency of automatic and sustained automatic outages per circuit and per hundred kilometers, outage duration, and an element unavailability) that are needed to perform any type of probabilistic reliability studies. Also, these 6-year collected outage data are used to assess and benchmark the reliability performance of a system’s zones. The importance of these kinds of data and analysis for reliability applications is stressed.
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