DocumentCode :
1389219
Title :
Torsional system parameter identification of turbine-generator sets
Author :
Brown, M.D. ; Grande-Moran, C.
Author_Institution :
Dept. of Power Syst. Eng., GE Electr. Distribution & Control, Schenectady, NY, USA
Volume :
12
Issue :
4
fYear :
1997
fDate :
12/1/1997 12:00:00 AM
Firstpage :
304
Lastpage :
309
Abstract :
Accurate low order linear models that represent the torsional motion of turbine-generator sets are needed for determining shaft torsional responses resulting from subsynchronous resonance conditions, electric system faults and planned/unplanned switching actions in the electric network. This paper outlines the theoretical background and the methodology used for identification of linear state-space models of turbine-generator systems. These analytic mass-spring-damper models are lumped-parameter approximations, which in reality represent a continuous nonlinear system. For transient torque studies these models are adequate representations of the torsional dynamics of interest. Reduced analytic models of any particular turbine-generator unit, however, usually do not match precisely the behavior of the real machine. The paper describes an optimization method that can give a more precise representation of a particular turbine-generator based on actual plant tests and an assumed model of that unit. The parameter identification process is illustrated using plant test data from a 618 MVA turbine-generator unit
Keywords :
machine theory; optimisation; parameter estimation; state-space methods; subsynchronous resonance; torsion; turbogenerators; 618 MVA; continuous nonlinear system; linear state-space models; low order linear models; lumped-parameter approximations; mass-spring-damper models; optimization method; parameter identification process; power system faults; shaft torsional responses; subsynchronous resonance conditions; torsional motion; torsional system parameter identification; turbine-generator sets; Magnetic resonance; Mesh generation; Nonlinear dynamical systems; Optimization methods; Parameter estimation; Power system modeling; Power system transients; Shafts; Testing; Torque;
fLanguage :
English
Journal_Title :
Energy Conversion, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8969
Type :
jour
DOI :
10.1109/60.638865
Filename :
638865
Link To Document :
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