A New Application of Mayfly Optimization Algorithm for Parameter Estimation of Single-Phase Transformer

Abstract

In this paper, the Mayfly Optimization algorithm (MA) is proposed to identify the parameters of the single-phase power transformer which is considered as one of the electric engineering optimization problems. This study aims to estimate equivalent circuit parameters of a single-phase transformer using current and voltage values at any known load. The difference between actual and estimated parameter values has been minimized using the MA technique and obtaining the best values for these parameters. The optimum value of the errors between the measured and the estimated values of the primary current, secondary current, and secondary voltage at full load using the proposed MA algorithm was compared with three other algorithms (Particle Swarm Optimization (PSO), Differential Evolution (DE) and Shuffled frog-leaping algorithm (SFLA)). The obtained results confirm that the proposed technique can be used for single-phase transformer parameters identification.