Wind speed forecasting techniques for maximum power point tracking control in variable speed wind turbine generator. (2nd October 2019)

• Record Type: Journal Article
• Authors: Achouri, Fouzia; Mendil, Boubekeur
• Is Part Of: International journal of modelling & simulation. Volume 39:Number 4(2019)
• Page Start: 246
• Page End: 255
• Publication Date: 2019-10-02
• Subjects: Maximum power point tracking -- wind turbine -- adaptive linear neural network -- fuzzy logic -- extended Kalman filter -- variable speed; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2019.1572691
• Languages: English
• ISSNs: 0228-6203

Abstract

ABSTRACT: The main consideration of this paper is focused on the estimation of the wind speed in variable speed wind turbine that drives a permanent magnet synchronous generator. Intelligent approaches are used for the performance improvement of the control system to track the maximum possible of wind power. First, a mathematical model of wind turbine at variable speeds is established. The traditional Extended Kalman estimator is applied, and then; Adaptive Linear neural network and fuzzy logic estimators are developed and compared with the classical algorithm. The presented simulation results demonstrate the performances improvement of the control system using the intelligent estimators compared to the conventional one. Abbreviations: MPPT: Maximum Power Point Tracking; ADALINE: Adaptive Linear Neural Network; FL: Fuzzy Logic; EKF: Extended Kalman Filter