Advanced control strategies for small wind turbine MPPT and stress reduction

Abstract

This thesis demonstrates the functionality of a single-input single-output adaptive predictive control(APC) strategy , focused on power tracking and stress reduction. A modified recursive least squares algorithm was designed to improve the adaptive mechanism and eliminate poor sensitivity malfunctions and a estimator wind up problem. The real implementation of the modification shows a high improvement in the adaptive mechanism’s reliability and the certainty of its estimations. An objective function that combines stress and power was designed and tested. Results indicate that the function achieves an important stress reduction with a slight decrement on power, therefore, validating the design. The performance of the APC and a proportional, integral and derivate (PID) controller following the objetive function under different conditions was analyzed and compared. The system was tested under a constant and a variable wind input with different configurations i.e. a wind series with gust or no presence and with a high or low turbulence with possible wind mean speed values of 6 m/s and 8 m/s.Experimental results show the APC’s tracking error in power, stress and voltage is significantly lower than the one obtained using the PID controller. The variable wind speed ws achieved using a LabVIEW application that sends information to an Arduino Due microcontroller that executes the control algorithms.