Fühler-im-Netz: A smart grid and power line communication data set

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
IET Smart Grid Pub Date : 2022-11-06 DOI:10.1049/stg2.12093
Christoph Balada, Sheraz Ahmed, Andreas Dengel, Max Bondorf, Nikolai Hopfer, Markus Zdrallek
{"title":"Fühler-im-Netz: A smart grid and power line communication data set","authors":"Christoph Balada,&nbsp;Sheraz Ahmed,&nbsp;Andreas Dengel,&nbsp;Max Bondorf,&nbsp;Nikolai Hopfer,&nbsp;Markus Zdrallek","doi":"10.1049/stg2.12093","DOIUrl":null,"url":null,"abstract":"<p>The increasing complexity of low-voltage networks poses a growing challenge for the reliable and fail-safe operation of electricity grids. The reasons for this include an increasingly decentralised energy generation (photovoltaic systems, wind power etc.) and the emergence of new types of consumers (e-mobility, domestic electricity storage etc.). At the same time, the low-voltage grid is largely unmonitored and local power failures are sometimes hard to detect. To overcome this, power line communication (PLC) has emerged as a potential solution for reliable monitoring of the low-voltage grid. In addition to establishing a communication infrastructure, PLC also offers the possibility of evaluating the cables themselves, as well as the connection quality between individual cable distributors based on their signal-to-noise ratio (SNR). The roll-out of a large-scale PLC infrastructure therefore not only ensures communication, but also introduces a tool for monitoring the entire network. To evaluate the potential of this data, we installed 38 PLC modems in three different areas of a German city with a population of about 150,000 as part of the Fühler-im-Netz (FiN) project. Over a period of 22 months, an SNR spectrum of each connection between adjacent PLC modems was generated every quarter of an hour. The availability of this real-world PLC data opens up new possibilities to react to the increasingly complex challenges in future smart grids. This paper provides a detailed analysis of the data generation and describes how the data was collected during normal operation of the electricity grid. In addition, we present common anomalies, effects, and trends that could be observed in the PLC data at daily, weekly, or seasonal levels. Finally, we discuss potential use cases and the remote inspection of a cable section is highlighted as an example.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12093","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Smart Grid","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/stg2.12093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 1

Abstract

The increasing complexity of low-voltage networks poses a growing challenge for the reliable and fail-safe operation of electricity grids. The reasons for this include an increasingly decentralised energy generation (photovoltaic systems, wind power etc.) and the emergence of new types of consumers (e-mobility, domestic electricity storage etc.). At the same time, the low-voltage grid is largely unmonitored and local power failures are sometimes hard to detect. To overcome this, power line communication (PLC) has emerged as a potential solution for reliable monitoring of the low-voltage grid. In addition to establishing a communication infrastructure, PLC also offers the possibility of evaluating the cables themselves, as well as the connection quality between individual cable distributors based on their signal-to-noise ratio (SNR). The roll-out of a large-scale PLC infrastructure therefore not only ensures communication, but also introduces a tool for monitoring the entire network. To evaluate the potential of this data, we installed 38 PLC modems in three different areas of a German city with a population of about 150,000 as part of the Fühler-im-Netz (FiN) project. Over a period of 22 months, an SNR spectrum of each connection between adjacent PLC modems was generated every quarter of an hour. The availability of this real-world PLC data opens up new possibilities to react to the increasingly complex challenges in future smart grids. This paper provides a detailed analysis of the data generation and describes how the data was collected during normal operation of the electricity grid. In addition, we present common anomalies, effects, and trends that could be observed in the PLC data at daily, weekly, or seasonal levels. Finally, we discuss potential use cases and the remote inspection of a cable section is highlighted as an example.

Abstract Image

hler‐im‐Netz:智能电网和电力线通信数据集
低压电网的复杂性日益增加,对电网的可靠性和故障安全运行提出了越来越大的挑战。其原因包括日益分散的能源生产(光伏系统,风力发电等)和新型消费者(电动汽车,国内电力储存等)的出现。与此同时,低压电网在很大程度上是不受监控的,局部电力故障有时很难检测到。为了克服这一点,电力线通信(PLC)已经成为可靠监测低压电网的潜在解决方案。除了建立通信基础设施外,PLC还提供了评估电缆本身的可能性,以及基于其信噪比(SNR)的单个电缆分销商之间的连接质量。因此,大规模PLC基础设施的推出不仅确保了通信,而且还引入了监控整个网络的工具。为了评估这些数据的潜力,我们在一个人口约15万的德国城市的三个不同区域安装了38个PLC调制解调器,作为f hler-im- netz (FiN)项目的一部分。在22个月的时间里,每隔一刻钟产生一个相邻PLC调制解调器之间每个连接的信噪比频谱。这些真实世界PLC数据的可用性为应对未来智能电网日益复杂的挑战开辟了新的可能性。本文对数据的产生进行了详细的分析,并介绍了如何在电网正常运行时收集数据。此外,我们提出了常见的异常现象、影响和趋势,可以在PLC数据中观察到每日、每周或季节性水平。最后,我们讨论了潜在的用例,并强调了电缆部分的远程检查作为一个例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
×
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