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Vahid Rashtchi

Rashtchi V; Rahimpour E; Rezapour EM
Using a genetic algorithm for parameter identification of transformer R-L-C-M model

The R-L-C-M model of power transformer is obtained from geometrical structure and is extremely appropriate for studying transient phenomena in a transformer and detecting mechanical faults. The precision of this model depends strongly on the precision of its parameters. The accuracy of these parameters that are calculated by analytical formulas is limited due to different reasons. In this paper a genetic algorithm (GA) is introduced as a method to identify the parameters of R-L-C-M Model without employing any analytical formulas.



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