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Title: Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses

Abstract

An alternative approach to characterise real voltage dips is proposed and evaluated in this study. The proposed methodology is based on voltage-space vector solutions, identifying parameters for ellipses trajectories by using the least-squares algorithm applied on a sliding window along the disturbance. The most likely patterns are then estimated through a clustering process based on the k-means algorithm. The objective is to offer an efficient and easily implemented alternative to characterise faults and visualise the most likely instantaneous phase-voltage evolution during events through their corresponding voltage-space vector trajectories. This novel solution minimises the data to be stored but maintains extensive information about the dips including starting and ending transients. The proposed methodology has been applied satisfactorily to real voltage dips obtained from intensive field-measurement campaigns carried out in a Spanish wind power plant up to a time period of several years. A comparison to traditional minimum root mean square-voltage and time-duration classifications is also included in this study.

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1402556
Report Number(s):
NREL/JA-5D00-70343
Journal ID: ISSN 1752-1416
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: IET Renewable Power Generation; Journal Volume: 11; Journal Issue: 10
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; voltage dips; power supply; vectors

Citation Formats

García-Sánchez, Tania, Gómez-Lázaro, Emilio, Muljadi, E., Kessler, Mathieu, and Molina-García, Angel. Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses. United States: N. p., 2017. Web. doi:10.1049/iet-rpg.2016.0813.
García-Sánchez, Tania, Gómez-Lázaro, Emilio, Muljadi, E., Kessler, Mathieu, & Molina-García, Angel. Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses. United States. doi:10.1049/iet-rpg.2016.0813.
García-Sánchez, Tania, Gómez-Lázaro, Emilio, Muljadi, E., Kessler, Mathieu, and Molina-García, Angel. 2017. "Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses". United States. doi:10.1049/iet-rpg.2016.0813.
@article{osti_1402556,
title = {Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses},
author = {García-Sánchez, Tania and Gómez-Lázaro, Emilio and Muljadi, E. and Kessler, Mathieu and Molina-García, Angel},
abstractNote = {An alternative approach to characterise real voltage dips is proposed and evaluated in this study. The proposed methodology is based on voltage-space vector solutions, identifying parameters for ellipses trajectories by using the least-squares algorithm applied on a sliding window along the disturbance. The most likely patterns are then estimated through a clustering process based on the k-means algorithm. The objective is to offer an efficient and easily implemented alternative to characterise faults and visualise the most likely instantaneous phase-voltage evolution during events through their corresponding voltage-space vector trajectories. This novel solution minimises the data to be stored but maintains extensive information about the dips including starting and ending transients. The proposed methodology has been applied satisfactorily to real voltage dips obtained from intensive field-measurement campaigns carried out in a Spanish wind power plant up to a time period of several years. A comparison to traditional minimum root mean square-voltage and time-duration classifications is also included in this study.},
doi = {10.1049/iet-rpg.2016.0813},
journal = {IET Renewable Power Generation},
number = 10,
volume = 11,
place = {United States},
year = 2017,
month = 8
}
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