Trend analysis for power quality parameters based on long-term measurement campaigns

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung


Power grids face significant changes, like increase of renewables or large-scale introduction of electric vehicles. This has a significant impact on Power Quality and consequently network operators install an increasing number of Power Quality instruments to monitor their networks. To analyse these large amounts of data in an efficient way, automatic data mining methods are required. This paper presents a method to identify long-term trends in time series of continuous Power Quality parameters, which can support network operators with the early detection of fundamental changes in Power Quality levels. This information can e.g. support the asset management or network planning in optimizing the costs for managing Power Quality levels. The method is applied to field measurements (3 years at 24 sites) taken from Chinese and German 110-kV-network.


Titel2022 20th International Conference on Harmonics & Quality of Power (ICHQP)
ISBN (elektronisch)978-1-6654-1639-9
PublikationsstatusVeröffentlicht - 29 Mai 2022


ReiheInternational Conference on Harmonics and Quality of Power

Externe IDs

Scopus 85133757295
Mendeley a85cf75f-2f57-3906-9dce-5111a5d03606
unpaywall 10.1109/ichqp53011.2022.9808645


Forschungsprofillinien der TU Dresden

Ziele für nachhaltige Entwicklung


  • Data mining, Power quality, Time series analysis, Trend identification