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Robust and fast state estimation for poorly-observable low voltage distribution networks based on the Kalman filter algorithm
ID
Antončič, Mitja
(
Author
),
ID
Papič, Igor
(
Author
),
ID
Blažič, Boštjan
(
Author
)
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https://www.mdpi.com/1996-1073/12/23/4457
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Abstract
This paper presents a novel approach for the state estimation of poorly-observable low voltage distribution networks, characterized by intermittent and erroneous measurements. The developed state estimation algorithm is based on the Extended Kalman filter, where we have modified the execution of the filtering process. Namely, we have fixed the Kalman gain and Jacobian matrices to constant matrices; their values change only after a larger disturbance in the network. This allows for a fast and robust estimation of the network state. The performance of the proposed state-estimation algorithm is validated by means of simulations of an actual low-voltage network with actual field measurement data. Two different cases are presented. The results of the developed state estimator are compared to a classical estimator based on the weighted least squares method. The comparison shows that the developed state estimator outperforms the classical one in terms of calculation speed and, in case of spurious measurements errors, also in terms of accuracy.
Language:
English
Keywords:
state estimation
,
low voltage
,
poor observability
,
Kalman
,
forecast-aided state estimator
,
weighted least squares
,
low-voltage state esimator
,
low-voltage state estimation
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2019
Number of pages:
18 str.
Numbering:
Vol. 12, iss. 23, art. 4457
PID:
20.500.12556/RUL-133134
UDC:
621.31
ISSN on article:
1996-1073
DOI:
10.3390/en12234457
COBISS.SI-ID:
12765012
Publication date in RUL:
12.11.2021
Views:
1094
Downloads:
190
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Record is a part of a journal
Title:
Energies
Shortened title:
Energies
Publisher:
Molecular Diversity Preservation International
ISSN:
1996-1073
COBISS.SI-ID:
518046745
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:
01.12.2019
Secondary language
Language:
Slovenian
Keywords:
ocenjevanje stanja
,
nizka napetost
,
slaba spoznavnost
,
Kalman
,
ocenjevanje stanja z napovedovanjem
,
uteženi najmanjši kvadrati
,
nizkonapetostni ocenjevalnik stanja
Projects
Funder:
ARRS - Slovenian Research Agency
Funding programme:
Young researchers
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