Unscented Kalman filter for power system dynamic state estimation

G. Valverde, V. Terzija

Research output: Contribution to journalArticlepeer-review

289 Citations (SciVal)

Abstract

A new estimation method for power system dynamic state estimation, the unscented Kalman filter (UKF), is presented. It is based on the application of the unscented transformation (UT) combined with the Kalman filter theory. One of the challenges in the process of power system estimation is coping with a highly non-linear mathematical model of network equations, which is usually approximated through a linearisation. The new derivative free estimation method overcomes this limitation using the UT and achieves better accuracy with simpler implementation. The UKF is derived and demonstrated using three different test power systems under typical network and measurement conditions. Its performance is compared with the classical extended Kalman filter. The simplicity of the new estimator and its low computational demand make it a better option to be applied in the next generation of dynamic system estimators.

Original languageEnglish
Pages (from-to)29-37
Number of pages9
JournalIET Generation, Transmission and Distribution
Volume5
Issue number1
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes

Fingerprint

Dive into the research topics of 'Unscented Kalman filter for power system dynamic state estimation'. Together they form a unique fingerprint.

Cite this