Seasonal variations in long-term measurements of power quality parameters

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

Abstract

Power quality levels in public low voltage grids are influenced by many factors which can either be assigned to the electrical environment (connected consumers, connected generation, network characteristics) or to the non-electrical environment (e.g. climatic conditions) at the measurement site. Type and amount of connected consumers (consumer topology) are expected to have a very high impact on power quality (PQ) levels. The usage behaviour of equipment by customers usually varies over the year. Subsequently the levels of PQ parameters like harmonics may show a seasonal variation. The aim of the paper is the identification and quantification of these seasonal variations. It starts with a systematic overview of major factors impacting Power Quality levels and continues with the classification of the typical types of their variation (short-term, medium-term and long-term). Next a two-stage approach based on time series decomposition is introduced in order to quantify seasonal variations by a set of indices. Finally several existing long-term measurements of public LV grids lasting more than one year are selected for a comprehensive illustration of the method. The sites represent different consumer topologies, like shops, offices and residential areas. Seasonal variations are quantified in detail for these sites and selected current quality parameters.

Details

OriginalspracheUndefiniert
Titel2015 IEEE Eindhoven PowerTech
Seiten1-6
Seitenumfang6
PublikationsstatusVeröffentlicht - 1 Juni 2015
Peer-Review-StatusJa

Externe IDs

Scopus 84951320121
ORCID /0000-0001-5951-2033/work/142241881
ORCID /0000-0001-8439-7786/work/142244166

Schlagworte

Schlagwörter

  • harmonics, time series analysis, power quality, Power quality, Harmonic analysis, Current measurement, Indexes, Network topology, Topology, Time series analysis, Consumer behavior, discrete fourier transforms