Title :
Identification of magnetizing inrush current in power transformers using GSA trained ANN for educational purposes
Author :
Taghipour, M. ; Moradi, A.R. ; Yazdani-Asrami, M.
Author_Institution :
Dept. of Electr. Eng., Univ. of Birjand, Birjand, Iran
Abstract :
Inrush current in transformers is generated when transformer cores are driven into saturation during no-load energization. This current consists of high amplitude, large DC component and also, has much 2nd harmonic content. In the proposed paper, a new computer-aided simulation technique for teaching inrush current principles and its discrimination from normal current based on artificial intelligence has been introduced. This method can be used for educating concepts of inrush current and its identification techniques during undergraduate curriculum as an excellent approach. Evaluation of the proposed approach with undergraduate senior students is very useful in terms of their understanding of the inrush current concepts.
Keywords :
computer aided instruction; learning (artificial intelligence); power engineering education; power transformers; transformer cores; GSA trained ANN; artificial intelligence; computer-aided simulation technique; educational purposes; gravitational search algorithm; magnetizing inrush current identification; no-load energization; power transformers; transformer cores; undergraduate curriculum; Artificial neural networks; Circuit faults; Neurons; Power transformers; Saturation magnetization; Surge protection; Surges; Artificial Neural Network (ANN); Gravitational Search Algorithm (GSA); Magnetizing Inrush Current; Transformer;
Conference_Titel :
Open Systems (ICOS), 2010 IEEE Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9193-3
DOI :
10.1109/ICOS.2010.5720058
