Dip fault detection and identification for wind conversion energy system

This paper addresses the problem of detecting voltage dips in Wind Turbine Generator connected to electrical grid. A procedure based on analysis of voltage indicators is proposed. It used the artificial neural network in order to extract the features (magnitudes and angle of each phase).

The method is tested in simulation and the results approved its efficiency and rapidity. It could not only detect the dipfault but also identify the type of fault.