Non-invasive identification of turbogenerator parameters from actual transient network data

Greame Hutchison*, Bashar Zahawi, Keith Harmer, Shady Gadoue, Damian Giaouris

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Synchronous machines are the most widely used form of generators in electrical power systems. Identifying the parameters of these generators in a non-invasive way is very challenging because of the inherent non-linearity of power station performance. This study proposes a parameter identification method using a stochastic optimisation algorithm that is capable of identifying generator, exciter and turbine parameters using actual network data. An eighth order generator/turbine model is used in conjunction with the measured data to develop the objective function for optimisation. The effectiveness of the proposed method for the identification of turbo-generator parameters is demonstrated using data from a recorded network transient on a 178 MVA steam turbine generator connected to the UK's national grid.

Original languageEnglish
Pages (from-to)1129-1136
Number of pages8
JournalIET Generation, Transmission and Distribution
Volume9
Issue number11
Early online date27 Feb 2015
DOIs
Publication statusPublished - 6 Aug 2015

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Bibliographical note

This paper is a postprint of a paper submitted to and accepted for publication in IET Generation, Transmission & Distribution and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library

Cite this

Hutchison, G., Zahawi, B., Harmer, K., Gadoue, S., & Giaouris, D. (2015). Non-invasive identification of turbogenerator parameters from actual transient network data. IET Generation, Transmission and Distribution, 9(11), 1129-1136. https://doi.org/10.1049/iet-gtd.2014.0481