Difference between revisions of "Projects:2016s1-121 Measurement of Transformer Parameters"
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This project is identifying a semi-automated method to perform best estimate of transformer parameters. The aim of the project is to use two-port network model to estimate the parameters for any transformer model using transmission parameters with less variable. The obtained data are analysed and compared with the corresponding values in different methods. It starts from an ideal and simplified transformer models, which applies one-port network on the transformer to be tested. The method of least squares is applied to obtain the best estimate input variables The optimization techniques, Lagrange Multiplier is also applied to minimise any discrepancy between the observed behaviour of a transformer and the predicted behaviour of the model. Analysis of non-linearity effects on transformer is the rest part of the project which involves identifying the characteristics in terms of magnetic field and current. | This project is identifying a semi-automated method to perform best estimate of transformer parameters. The aim of the project is to use two-port network model to estimate the parameters for any transformer model using transmission parameters with less variable. The obtained data are analysed and compared with the corresponding values in different methods. It starts from an ideal and simplified transformer models, which applies one-port network on the transformer to be tested. The method of least squares is applied to obtain the best estimate input variables The optimization techniques, Lagrange Multiplier is also applied to minimise any discrepancy between the observed behaviour of a transformer and the predicted behaviour of the model. Analysis of non-linearity effects on transformer is the rest part of the project which involves identifying the characteristics in terms of magnetic field and current. |
Revision as of 13:55, 26 October 2016
Project Title
Measurement of Transformer Parameters
Student Name
Chen Qiao Rahel Bekele Megersa
Supervisors
Dr. Andrew Alison Dr. Rastko Zivanovic
Abstract
This project is identifying a semi-automated method to perform best estimate of transformer parameters. The aim of the project is to use two-port network model to estimate the parameters for any transformer model using transmission parameters with less variable. The obtained data are analysed and compared with the corresponding values in different methods. It starts from an ideal and simplified transformer models, which applies one-port network on the transformer to be tested. The method of least squares is applied to obtain the best estimate input variables The optimization techniques, Lagrange Multiplier is also applied to minimise any discrepancy between the observed behaviour of a transformer and the predicted behaviour of the model. Analysis of non-linearity effects on transformer is the rest part of the project which involves identifying the characteristics in terms of magnetic field and current.