Time-domain voltage sag state estimation based on the unscented Kalman filter for power systems with nonlinear components

Rafael Cisneros-Magañia, Aurelio Medina, Olimpo Anaya-Lara

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper proposes a time-domain methodology based on the unscented Kalman filter to estimate voltage sags and their characteristics, such as magnitude and duration in power systems represented by nonlinear models. Partial and noisy measurements from the electrical network with nonlinear loads, used as data, are assumed. The characteristics of voltage sags can be calculated in a discrete form with the unscented Kalman filter to estimate all the busbar voltages; being possible to determine the rms voltage magnitude and the voltage sag starting and ending time, respectively. Voltage sag state estimation results can be used to obtain the power quality indices for monitored and unmonitored busbars in the power grid and to design adequate mitigating techniques. The proposed methodology is successfully validated against the results obtained with the time-domain system simulation for the power system with nonlinear components, being the normalized root mean square error less than 3%.
LanguageEnglish
Number of pages20
JournalEnergies
Volume11
Issue number6
DOIs
Publication statusPublished - 1 Jun 2018

Fingerprint

Voltage Sag
State Estimation
State estimation
Kalman filters
Power System
Kalman Filter
Time Domain
Electric potential
Busbars
Voltage
Electrical Networks
Power Quality
Methodology
System Simulation
Mean square error
Estimate
Nonlinear Model
Roots
Power quality
Grid

Keywords

  • nonlinear dynamic system
  • power quality
  • power system simulation
  • state estimation
  • unscented Kalman filter
  • voltage fluctuation

Cite this

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abstract = "This paper proposes a time-domain methodology based on the unscented Kalman filter to estimate voltage sags and their characteristics, such as magnitude and duration in power systems represented by nonlinear models. Partial and noisy measurements from the electrical network with nonlinear loads, used as data, are assumed. The characteristics of voltage sags can be calculated in a discrete form with the unscented Kalman filter to estimate all the busbar voltages; being possible to determine the rms voltage magnitude and the voltage sag starting and ending time, respectively. Voltage sag state estimation results can be used to obtain the power quality indices for monitored and unmonitored busbars in the power grid and to design adequate mitigating techniques. The proposed methodology is successfully validated against the results obtained with the time-domain system simulation for the power system with nonlinear components, being the normalized root mean square error less than 3{\%}.",
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Time-domain voltage sag state estimation based on the unscented Kalman filter for power systems with nonlinear components. / Cisneros-Magañia, Rafael; Medina, Aurelio; Anaya-Lara, Olimpo.

In: Energies, Vol. 11, No. 6, 01.06.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Time-domain voltage sag state estimation based on the unscented Kalman filter for power systems with nonlinear components

AU - Cisneros-Magañia, Rafael

AU - Medina, Aurelio

AU - Anaya-Lara, Olimpo

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AB - This paper proposes a time-domain methodology based on the unscented Kalman filter to estimate voltage sags and their characteristics, such as magnitude and duration in power systems represented by nonlinear models. Partial and noisy measurements from the electrical network with nonlinear loads, used as data, are assumed. The characteristics of voltage sags can be calculated in a discrete form with the unscented Kalman filter to estimate all the busbar voltages; being possible to determine the rms voltage magnitude and the voltage sag starting and ending time, respectively. Voltage sag state estimation results can be used to obtain the power quality indices for monitored and unmonitored busbars in the power grid and to design adequate mitigating techniques. The proposed methodology is successfully validated against the results obtained with the time-domain system simulation for the power system with nonlinear components, being the normalized root mean square error less than 3%.

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