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


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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Electrical and Electronic Engineering
College of Engineering & Physical Sciences > Power Electronics, Machines and Power System (PEMPS)
College of Engineering & Physical Sciences
Additional Information: 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
Uncontrolled Keywords: Control and Systems Engineering,Energy Engineering and Power Technology,Electrical and Electronic Engineering
Publication ISSN: 1751-8687
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2015-08-06
Published Online Date: 2015-02-27
Authors: Hutchison, Greame
Zahawi, Bashar
Harmer, Keith
Gadoue, Shady
Giaouris, Damian



Version: Accepted Version

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