Automatic Identification of Different Types of Consumer Configurations by Using Harmonic Current Measurements
Journal article, 2021
method can support network operators in the identification of consumer configurations and the early detection of fundamental changes in harmonic emission behaviour. This enables, for example, assistance in resolving customer complaints or supporting network planning by managing PQ levels using typical harmonic emission profiles.
public low voltage network
machine learning
support vector machines
time series
power system harmonics
harmonic current emission
consumer behavior
classification
Author
Max Domagk
Technische Universität Dresden
Irene Yu-Hua Gu
Chalmers, Electrical Engineering
Jan Meyer
Technische Universität Dresden
Peter Schegner
Technische Universität Dresden
Applied Sciences (Switzerland)
20763417 (eISSN)
Vol. 11 8 3598Areas of Advance
Energy
Subject Categories
Energy Systems
Other Electrical Engineering, Electronic Engineering, Information Engineering
DOI
10.3390/app11083598