Inverse Propagation Method of CT Distortion Current Under DC Bias Based on RFC-SAGA-RBF
The DC bias current in the transmission line can easily cause the saturation of current transformer(CT)and the harmonic components contained in the secondary current output of CT in saturation state will lead to an increase in power energy metering error.In order to improve the accuracy of current transformer measurement under DC bias,an inverse propagation method is proposed for CT distortion current.In this method,the inverse propagation process of CT distortion current under DC bias is divided into two stages:off-grid and on-grid.In the off-grid stage,the data sample set is generated by changing the operating environment of CT,and then the saturation degree of CT is classified by random forest classification(RFC)algorithm.Finally,a simulate anneal genetic algorithm-radial basis function(SAGA-RBF)model is trained for each subclass to simulate the saturation current.In the on-grid stage,the saturation data segment of the secondary current waveform is extracted by wavelet transform,and then the saturation data segment is input into the off-line model to realize the inverse propagation of the secondary distorted current.The simulation results show that the proposed method can relike the inverse propagation of the primary side current,and improve the measurement ac-curacy of CT.
electromagnetic current transformerDC biassaturation current reconstructionwavelet transformRFC algorithm
万方数据
维普
