Engineering Commons^™

Neural Network-Based Fault Distance Estimation For Multi-Terminal Dc Microgrids, Mohamed Elmadawy, Abdelhady Ghanem, Sayed Abulanwar, Ahmed Shahin

Mansoura Engineering Journal

Fault distance estimation in DC microgrids is a critical issue due to the growing adoption of DC-based distribution systems. Current methods face limitations like sensitivity to system parameters and high-resistance fault detection, necessitating improved accuracy. This study proposes a neural network approach to accurately locate fault distances in multi-terminal DC microgrids. Three different structures based on backpropagation algorithms are developed and trained to estimate fault distances with high precision. These structures can handle various fault scenarios, including different fault resistances and the presence of noise. Two of the structures can predict fault distances from one side locally, achieving low error …