Open AccessTime‐domain harmonic state estimation of nonlinear load power systems with under‐determined condition based on the extended Kalman filter
Author(s) -
CisnerosMagaña Rafael,
Medina Aurelio,
AnayaLara Olimpo
Publication year - 2017
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2242
Subject(s) - kalman filter , control theory (sociology) , nonlinear system , harmonic , extended kalman filter , time domain , state (computer science) , computer science , estimation , moving horizon estimation , power (physics) , electric power system , mathematics , engineering , acoustics , algorithm , physics , artificial intelligence , control (management) , quantum mechanics , computer vision , systems engineering
Summary 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. Copyright © 2016 John Wiley & Sons, Ltd.