Modeling and Linearization of DFIG Based Wind Turbine

Abstract

Usage level of wind units in power systems is increasing rapidly. There are different kinds of wind turbine generator. The Doubly-Fed Induction Generator (DFIG), is one of the most widely used electrical machines in the megawatt-class wind turbines. In a DFIG-based wind turbine, the stator is connected to grid directly while the rotor is connected a back-to-back converter via slip rings. Current sensor fault diagnosis for renewable power of wind turbine based on DFIG has gained serious importance. In this work, mathematical modeling of DFIG is presented. Nonlinear state equations are linearized with Takagi-Sugeno (T-S) Local Models for current sensor fault diagnosis. Modelling error between linear and nonlinear model is minimized by heuristic approach on membership functions. A bank of observer-based residual generator system for fault diagnosis is created, so additive and gain faults of stator current sensors can be detected and isolated.