A fitting method of the magnitude-frequency characteristic of capacitance voltage transformer transformation ratio based on iterative weighted improved BP neural network
Aiming at the problem of large fitting error of the transformation ratio magnitude-frequency characteristic curve of capacitive voltage transformer (CVT), this paper proposes an iterative weighted improved BP neural network method based on BP neural network. When the characteristic curve is fitted, this method can not only ensure that the mean square error of the fitted curve meets the convergence condition, but also can effectively reduce the maximum error of the fitted curve. Example calculations show that this method reduces the maximum error of the CVT transformation ratio magnitude-frequency characteristic fitting curve by 24.45%.