Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Doubly Fed Wind Turbine Control Strategy Based on Non-Linear Wind Speed Uncertainty Prediction Model

Version 1 : Received: 21 November 2023 / Approved: 21 November 2023 / Online: 21 November 2023 (15:15:08 CET)

A peer-reviewed article of this Preprint also exists.

Ma, K.; Wang, R.; Nian, H.; Wang, X.; Fan, W. Nonlinear Model Predictive Control for Doubly Fed Induction Generator with Uncertainties. Appl. Sci. 2024, 14, 1818. Ma, K.; Wang, R.; Nian, H.; Wang, X.; Fan, W. Nonlinear Model Predictive Control for Doubly Fed Induction Generator with Uncertainties. Appl. Sci. 2024, 14, 1818.

Abstract

Doubly-fed induction generators (DFIG) find extensive application in variable-speed wind power plants, providing notable advantages such as cost-effectiveness, operational flexibility across varying speeds, and enhanced power quality. This research focuses on the control of DFIGs employed in variable-speed wind turbine configurations. A suitable mathematical model is chosen for representative systems following a comprehensive review of contemporary research. Subsequent analysis reveals the instability of the open-loop time response of the system. To address this instability, the initial approach involves the implementation of the conventional Model Predictive Controller (MPC). However, the outcomes indicate that this controller falls short of delivering satisfactory performance despite the enhanced stability. In the subsequent phase, efforts are made to mitigate the impact of wind input variability by utilizing the Kalman filter, given its effectiveness in handling high variability. Following this, a novel methodology is introduced, which combines nonlinear MPC with the Lyapunov function. This method is based on the nonlinear model of the system. By using the Lyapunov function in the nonlinear MPC structure, the stability of the designed controller is guaranteed. The simulation results conducted using MATLAB software show that the output variables of the modeled DFIG system achieve stability within a reasonable timeframe applying the input.

Keywords

variable speed wind turbine; DFIG; Conventional MPC; Nonlinear MPC; Lyapunov function

Subject

Engineering, Electrical and Electronic Engineering

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