Automatic Identification of Different Types of Consumer Configurations by Using Harmonic Current Measurements
Source abstract
Abstract
Power quality (PQ) is an increasing concern in the distribution networks of modern industrialized countries. The PQ monitoring activities of distribution system operators (DSO), and consequently the amount of PQ measurement data, continuously increase, and consequently new and automated tools are required for efficient PQ analysis. Time characteristics of PQ parameters (e.g., harmonics) usually show characteristic daily and weekly cycles, mainly caused by the usage behaviour of electric devices. In this paper, methods are proposed for the classification of harmonic emission profiles for typical consumer configurations in public low voltage (LV) networks using a binary decision tree in combination with support vector machines. The performance of the classification was evaluated based on 40 different measurement sites in German public LV grids. This 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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Power Quality and Harmonics · Power Transformer Diagnostics and Insulation · Electricity Theft Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Electrical Power Systems and High Voltage Engineering, Technische Universitaet Dresden, 01062 Dresden, Germany
Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
Funding
Deutsche Forschungsgemeinschaft
References (39)
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