Smart Determination of Current Transformers Errors on the Basis of Core Material Characteristics

The possibility of determining the phase and current errors of an existing or newly designed current instrument transformer on the basis of special characteristics of the core material is examined. One of the characteristics represents the dependence between the magnetic field intensity on the core sheet surface, measured at the instant when induction is at its peak, and the mean peak induction in the cross section of the sheet. The other characteristic represents the dependence between the field intensity value measured at the instant when induction passes through zero and the peak induction value. The characteristics must be determined for the sinusoidal shape of the induction curve. The secondary winding of the current instrument transformer should be uniformly distributed along the core. One must know the following: the number of turns in the primary and secondary winding, respectively, the resistance of the secondary winding and the resistance at the secondary winding output when the primary current is being converted. Indicated relations provide a clear formula for designing effective current transformers. The main contribution of this paper is to present the method for estimating the parameters of current transformer a priori, relying on characteristics of the core material. However, this formula combined with elements of artificial intelligence—nature-inspired optimization algorithms—results in a convenient tool for optimal core geometry design. The paper presents an extension of the method to a smart design approach with application of the Birch-inspired Optimization Algorithm (BiOA).