DocumentCode
1486399
Title
Synchronous machine parameters from frequency-response finite-element simulations and genetic algorithms
Author
Escarela-Perez, Rafael ; Niewierowicz, Tadeusz ; Campero-Littlewood, Eduardo
Author_Institution
Univ. Autonoma Metropolitana, Mexico City, Mexico
Volume
16
Issue
2
fYear
2001
fDate
6/1/2001 12:00:00 AM
Firstpage
198
Lastpage
203
Abstract
This paper presents a novel way to obtain parameters of synchronous-machine equivalent circuits from standstill frequency response data using a hybrid genetic algorithm. The genetic algorithm is capable of finding a global minimum within a search interval of the fitness function used to match the equivalent circuit and the measured machine transfer functions, notwithstanding the initial guess of the identification process. Therefore, methods such as the maximum likelihood estimation technique, could be substantially enhanced. Results obtained in the identification procedure show that good matching can be obtained with either negative or positive leakage inductance values. These results cast some light on the possible physical meaning that circuit parameters may have. Finite-element modeling is used here to determine the transfer functions of a turbine generator. This approach is consistent with the general aim of obviating the requirement of field testing
Keywords
equivalent circuits; finite element analysis; frequency response; genetic algorithms; inductance; machine theory; maximum likelihood estimation; synchronous machines; transfer functions; equivalent circuit; equivalent circuits; finite-element modeling; fitness function; frequency-response finite-element simulations; genetic algorithms; good matching; hybrid genetic algorithm; identification procedure; identification process; machine transfer functions; maximum likelihood estimation technique; negative leakage inductance; positive leakage inductance; standstill frequency response data; synchronous machine parameters; turbine generator; Circuit testing; Equivalent circuits; Finite element methods; Frequency response; Genetic algorithms; Inductance; Maximum likelihood estimation; Synchronous machines; Transfer functions; Turbines;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/60.921473
Filename
921473
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