Harmonic disturbance location by applying Bayesian inference

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Abstract

Harmonic pollution is one of the most important power quality issues in electric power systems. Correct location of the main harmonic disturbance source is a key step to solve the problem. This paper presents a method to detect the location of harmonic disturbance source in low voltage network through Bayesian inference. The harmonic state is estimated based on the measurement data from limited measurement points whereby the measurement error is also considered. The performance of the proposed method is assessed through a case study applied in a typical low voltage network. Monte Carlo simulation is used to obtain the statistical results. The influence of different parameters like disturbance level, measurement accuracy level, etc. is discussed. The proposed method shows the adequacy for the analysis of distribution networks.
Original languageEnglish
Pages (from-to)886–894
JournalElectric Power Systems Research
Volume140
DOIs
Publication statusPublished - 2016

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Level measurement
Electric potential
Power quality
Electric power systems
Measurement errors
Electric power distribution
Pollution
Monte Carlo simulation

Cite this

@article{670762743bf94b8689653723800a8307,
title = "Harmonic disturbance location by applying Bayesian inference",
abstract = "Harmonic pollution is one of the most important power quality issues in electric power systems. Correct location of the main harmonic disturbance source is a key step to solve the problem. This paper presents a method to detect the location of harmonic disturbance source in low voltage network through Bayesian inference. The harmonic state is estimated based on the measurement data from limited measurement points whereby the measurement error is also considered. The performance of the proposed method is assessed through a case study applied in a typical low voltage network. Monte Carlo simulation is used to obtain the statistical results. The influence of different parameters like disturbance level, measurement accuracy level, etc. is discussed. The proposed method shows the adequacy for the analysis of distribution networks.",
author = "G. Ye and Y. Xiang and V. Cuk and J.F.G. Cobben",
year = "2016",
doi = "10.1016/j.epsr.2016.04.016",
language = "English",
volume = "140",
pages = "886–894",
journal = "Electric Power Systems Research",
issn = "0378-7796",
publisher = "Elsevier",

}

Harmonic disturbance location by applying Bayesian inference. / Ye, G.; Xiang, Y.; Cuk, V.; Cobben, J.F.G.

In: Electric Power Systems Research, Vol. 140, 2016, p. 886–894.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Harmonic disturbance location by applying Bayesian inference

AU - Ye, G.

AU - Xiang, Y.

AU - Cuk, V.

AU - Cobben, J.F.G.

PY - 2016

Y1 - 2016

N2 - Harmonic pollution is one of the most important power quality issues in electric power systems. Correct location of the main harmonic disturbance source is a key step to solve the problem. This paper presents a method to detect the location of harmonic disturbance source in low voltage network through Bayesian inference. The harmonic state is estimated based on the measurement data from limited measurement points whereby the measurement error is also considered. The performance of the proposed method is assessed through a case study applied in a typical low voltage network. Monte Carlo simulation is used to obtain the statistical results. The influence of different parameters like disturbance level, measurement accuracy level, etc. is discussed. The proposed method shows the adequacy for the analysis of distribution networks.

AB - Harmonic pollution is one of the most important power quality issues in electric power systems. Correct location of the main harmonic disturbance source is a key step to solve the problem. This paper presents a method to detect the location of harmonic disturbance source in low voltage network through Bayesian inference. The harmonic state is estimated based on the measurement data from limited measurement points whereby the measurement error is also considered. The performance of the proposed method is assessed through a case study applied in a typical low voltage network. Monte Carlo simulation is used to obtain the statistical results. The influence of different parameters like disturbance level, measurement accuracy level, etc. is discussed. The proposed method shows the adequacy for the analysis of distribution networks.

U2 - 10.1016/j.epsr.2016.04.016

DO - 10.1016/j.epsr.2016.04.016

M3 - Article

VL - 140

SP - 886

EP - 894

JO - Electric Power Systems Research

JF - Electric Power Systems Research

SN - 0378-7796

ER -