Detection of Inrush and Internal Fault in Power Transformers Based on Bacterial Foraging Optimization

Abstract

Power Transformer protection from inrush current and internal fault current is a critical issue in power system as the obstacle lies in the precise and swift distinction between them. In this paper, the task of detecting inrush and internal fault in power transformers is formulated as an optimization problem and solved using Hyperbolic S-Transform Bacterial Foraging Optimization (HS-TBFO) technique. The Gaussian Frequency-based Hyperbolic S-Transform detects the faults at much earlier stage and therefore minimizes the computation cost by applying Cosine Hyperbolic S-Transform. Next, the Bacterial Foraging Optimization (BFO) technique has been proposed and has demonstrated the capability of identifying the maximum number of faults covered with minimum test cases and therefore improving the fault detection efficiency in an efficient manner.