Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

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

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Abstract

This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm are selected from the simulation of the propagated harmonics in the system with an under-determined condition of the measurement matrix. The state estimation results are compared against the actual time-domain system response; both results closely agree hence verifying the effectiveness of the EKF to solve the time-domain power system state estimation. Several sampling frequencies and measurement noise are applied to assess the effects on the state estimation process, the error covariance matrix, residuals and on the execution time
Original languageEnglish
Article numbere2242
JournalInternational Transactions on Electrical Energy Systems
Early online date15 Jul 2016
DOIs
Publication statusPublished - 1 Feb 2017

Fingerprint

Extended Kalman filters
State Estimation
State estimation
Power System
Kalman Filter
Time Domain
Harmonic
Estimation Algorithms
Covariance matrix
Execution Time
Sampling
Methodology
Output
Simulation

Keywords

  • extended Kalman filter
  • harmonics
  • noise
  • nonlinear network
  • sampling frequency
  • state estimation

Cite this

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title = "Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter",
abstract = "This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm are selected from the simulation of the propagated harmonics in the system with an under-determined condition of the measurement matrix. The state estimation results are compared against the actual time-domain system response; both results closely agree hence verifying the effectiveness of the EKF to solve the time-domain power system state estimation. Several sampling frequencies and measurement noise are applied to assess the effects on the state estimation process, the error covariance matrix, residuals and on the execution time",
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AU - Cisneros-Magaña, Rafael

AU - Medina, Aurelio

AU - Anaya-Lara, Olimpo

N1 - "This is the peer reviewed version of the following article: Cisneros-Magaña, R., Medina, A., & Anaya-Lara, O. (2017). Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter. International Transactions on Electrical Energy Systems, [e2242], which has been published in final form at https://dx.doi.org/10.1002/etep.2242. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."

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N2 - This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm are selected from the simulation of the propagated harmonics in the system with an under-determined condition of the measurement matrix. The state estimation results are compared against the actual time-domain system response; both results closely agree hence verifying the effectiveness of the EKF to solve the time-domain power system state estimation. Several sampling frequencies and measurement noise are applied to assess the effects on the state estimation process, the error covariance matrix, residuals and on the execution time

AB - This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm are selected from the simulation of the propagated harmonics in the system with an under-determined condition of the measurement matrix. The state estimation results are compared against the actual time-domain system response; both results closely agree hence verifying the effectiveness of the EKF to solve the time-domain power system state estimation. Several sampling frequencies and measurement noise are applied to assess the effects on the state estimation process, the error covariance matrix, residuals and on the execution time

KW - extended Kalman filter

KW - harmonics

KW - noise

KW - nonlinear network

KW - sampling frequency

KW - state estimation

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JF - International Transactions on Electrical Energy Systems

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