An adaptive neuro-fuzzy based methodology for harmonic analysis of a power transformer

The interfering nature of harmonics always causes various power quality issues that impacts on both efficiency, and expected transformer life. Optimal analysis of the three-phase core power transformers using harmonic spectrum can limit these power quality issues. This paper designs the Adaptive Neuro-Fuzzy Inference System (ANFIS) based model for the estimation of losses. Further optimal parameters selection of three-phase power transformer using iron and ferrite core materials. This paper demonstrates factors that deteriorate the power quality, responsible for harmonics distortions and inefficiency in power transformers. The proposed ANFIS based analysis provides an optimal solution to harmonic reduction and improves overall efficiency. Also, providing a comparative study of various core parameters that will be suitable for a three-phase core transformer. The proposed parameters are demonstrated for improving the overall transformer efficiency using iron and ferrite core material. ANSYS Maxwell simulation estimates the Total Harmonic Distortion (THD) and enhances THD in contributing to the optimal core material. The design of a three-phase power transformer and the performance evaluation of the proposed methodology performed in MATLAB simulation environment.

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Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).