LAUSR

This article investigates the inaccuracies of identifying parameters for a single-phase transformer. In addition, in this article, two new transformer parameter estimation algorithms based on recently developed optimization techniques, as well as an objective function, are proposed for the transformer parameter estimation to improve the estimation process and prevent inaccuracies and parameters mismatch with real parameters of the transformer. The proposed algorithms utilize manta ray foraging optimization and chaotic manta ray foraging optimization methods for the estimation of transformer parameters. Unlike the previously proposed methods in the literature, the proposed objective function in this article includes no-load losses in the estimation process. For the matter of comparison, the estimated parameters obtained by using the proposed optimization techniques and objective function are compared with the corresponding values obtained using the classical test procedure recommended by IEEE, as well as with the corresponding values obtained using the previously introduced methods in the literature. The usage of the proposed objective function guarantees the representation of the real copper and no-load losses in the estimated transformer parameters and ensures that the estimated transformer output characteristics are in very good agreement with the experimentally obtained curves. To prove the effectiveness of the proposed parameter estimation algorithms, experimental parameters identification tests are implemented, and the experimentally identified transformer parameters are compared with the estimated parameters and their correlation is studied.