An ARMAX-DFIG model based adaptive controller for a wind energy conversion system

Abstract

This paper presents design of an adaptive model predictive current controller for a Doubly-Fed Induction Generator (DFIG) based Wind Energy Conversion System (WECS). An Autoregressive Moving Average with Exogenous input (ARMAX) model is developed to represent the dynamics of DFIG. The parameter vector of DFIG is estimated by employing the recursive least square algorithm. A predictive current controller based on model predictive concept is designed for output current control of the Rotor Side Converter (RSC) to achieve the desired control performance. Extensive simulation studies are pursued by implementing the proposed controller in MATLAB/SIMULINK environment. The performance of the proposed Adaptive Predictive Current Controller (APCC) is evaluated under various operating conditions such as sub-synchronous speed, synchronous speed, and super-synchronous speed. The performances of the proposed controller are compared with that of the conventional MPC. It is found that the proposed controller exhibits superior performance in terms of improved reference tracking of rotor currents.