2012
DOI: 10.5923/j.ijee.20120203.08
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Optimized Modeling of Transformer in Transient State with Genetic Algorithm

Abstract: In this paper a straightforward model is proposed for transient analysis of transformers. The model is capable of representing the impedance or admittance characteristics of the transformer measured from the terminals under different terminal connections up to approximately 200 kHz. The model is simple, so that the simulation with this model is easy and fast. It is feasible to use the model as a two port element by network analysing. To estimation of model parameters genetic algorithm is used. Outset of all, t… Show more

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Cited by 4 publications
(5 citation statements)
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“…The results show that the neural network optimized by GA has higher diagnostic efficiency and accuracy than without GA. The transient state analysis and faults detection of SSTS using GA is proposed in [20]. The results demonstrated that the proposed optimized SSTS using GA has fair accuracy for fault detection.…”
Section: Loadmentioning
confidence: 99%
“…The results show that the neural network optimized by GA has higher diagnostic efficiency and accuracy than without GA. The transient state analysis and faults detection of SSTS using GA is proposed in [20]. The results demonstrated that the proposed optimized SSTS using GA has fair accuracy for fault detection.…”
Section: Loadmentioning
confidence: 99%
“…The results obtained are very useful to correct errors and uncertainties of unidirectional impulse generators. In [31], analytical results are verified by means of numerical simulations.…”
Section: Modeling Based On Black Box Analysismentioning
confidence: 86%
“…In [49], the transformer winding parameters like R, L and C matrices were found using numerical methods for lightning tests. In [31], the transformer modeling is optimized using genetic algorithms and an important application in fault detection is discussed. Recent transformer models have been developed…”
Section: Previous Studiesmentioning
confidence: 99%
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