Unscented Kalman filter for power system dynamic state estimation

Author(s): G. Valverde and V. Terzija
DOI: 10.1049/iet-gtd.2010.0210

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Author(s): G. Valverde ¹ and V. Terzija ¹
- Affiliations: 1: School of Electrical and Electronic Engineering, University of Manchester, Manchester, UK
Source: Volume 5, Issue 1, January 2011, p. 29 – 37
DOI: 10.1049/iet-gtd.2010.0210 , Print ISSN 1751-8687, Online ISSN 1751-8695

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.

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Unscented Kalman filter for power system dynamic state estimation

Unscented Kalman filter for power system dynamic state estimation

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