DocumentCode
1282294
Title
Coherency-based low order models for shaft systems of turbine-generator sets
Author
Grande-Moran, C. ; Brown, M.D.
Author_Institution
Power Syst. Eng. Dept., GE Electr. Distribution & Control, Schenectady, NY, USA
Volume
12
Issue
3
fYear
1997
fDate
9/1/1997 12:00:00 AM
Firstpage
217
Lastpage
224
Abstract
Accurate low order lumped models that represent the low frequency torsional motion of turbine-generator sets are needed for determining shaft torsional responses resulting from subsynchronous resonance conditions, electric power system faults and planned/unplanned switching actions in the electric network. This paper presents a coherency-based method that resolves a high order inertia-spring lumped model into a low order inertia-spring lumped model, while preserving the selected group of natural torsional frequencies and their associated mode shapes. Forced eigen-frequency matching and conservation of angular momentum form the basis of the iterative procedure developed in the paper. Numerical examples are included to illustrate the capabilities of the proposed method in determining accurate low order dynamic equivalents
Keywords
eigenvalues and eigenfunctions; iterative methods; lumped parameter networks; machine theory; subsynchronous resonance; torsion; turbogenerators; angular momentum conservation; coherency-based low order models; forced eigen-frequency matching; iterative procedure; low frequency torsional motion; low order dynamic equivalents; low order inertia-spring lumped model; low order lumped models; natural torsional frequencies; power network switching actions; power system faults; shaft torsional responses; subsynchronous resonance; turbine-generator set shaft systems; Fatigue; Frequency; Power engineering and energy; Power generation; Power system dynamics; Power system modeling; Power system transients; Resonance; Shafts; Shape;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/60.629706
Filename
629706
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