Optimizing the Jiles–Atherton Model Parameters of Current Transformer by Genetic Algorithm

• Main Authors: Chiu-Tung Tsai, 蔡秋桐
• Other Authors: Sy-Ruen Hwang
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/06388423769541583649

碩士 === 逢甲大學 === 電機工程所 === 93 === Abstract When use conventional current transformer in the coupling coil assembly of the electric system, the iron core inside the coupling coil is usually made of silicon steel and in layered structure, thus to reduce the eddy current loss due to the cycled magnetic field. Since the layered iron core structure changes the original hysteresis characteristics, the hysteresis loops for the iron core of the simulated current transformer need an accurate model so that the accurate model could be used to analyze the protective relay of the electric system or the expected errors of the measuring and monitoring process. Therefore, the optimal parameters for the simulated hysteresis are important reference indices. Magnetic material is applicable to the problem of optimization for the genetic algorithm. The thesis used J-A model for iron hysteresis to establish a first order non-linear differential equation, and conducted simulated by using the genetic algorithm. The iterations, populations, chromosome genes, crossover ratio, and mutation ratio were set and substituted into the simulated equation to obtain the hysteresis loops with optimal parameters. The results were compared with the actual curves to observe the hysteresis loops change of the frequency change. This study used Matlab software to write the genetic algorithm of the penalty function to obtain the optimal solution for the parameters, and compared with the normal operating conditions to test the parameter change of current transformer hysteresis loops during electric system malfunctioning. The results were provided as reference to the protective relay of the electric system or the expected errors of the measuring and monitoring process.