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This paper proposes a method for voltage dip fault voltage detection and diagnosis in a grid connected Wind Turbine Generator. The method is data-driven. From the measurements of the currents flowing into the grid, three features related to the trajectory of the current vector in the Concordia stationary reference frame are extracted. The evaluation of the features for fault diagnosis is done through...
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...
This paper proposes a non-parametric method to detect grid voltage dip in a Wind Turbine Generator. The method is based on the analysis of the grid currents vector trajectory in the stationary reference frame. Two features (amplitude variation and angle deviation) are extracted for Fault Detection and Isolation. The approach is validated through simulation results of a Doubly Fed Induction Generator...
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