Sensorless control of PMSG in WECS using artificial neural network

Abstract

This paper presents an artificial neural network (ANN) observer for a speed sensorless permanent magnet synchronous generator (PMSG) in wind energy conversion system (WECS). In order to perform maximum power point tracking control of the wind generation system, it is necessary to drive wind turbine at an optimal rotor speed. From the aspect of reliability and increase in cost, wind velocity sensor is not preferred too. Wind and rotor speeds sensorless operating methods for wind generation system using observer are proposed only by measuring phase voltages and currents. Maximum wind energy extraction is achieved by running the wind turbine generator in variable-speed mode. The robustness of the ANN against stator resistance variation is studied.

RETRACTED: Artificial neural networks applications in wind energy systems: a review

“…Wind turbine power control [118][119][120][121][122] Reactive power control [123][124][125] Pitch control and prediction [126][127][128][129][130][131][132][133][134] MPPT Control [135][136][137][138][139][140][141][142] Voltage and frequency control [143][144][145] Optimal Control [146][147][148][149] Tip speed ratio and power factor prediction [150][151][152] C. Identification and evaluation Fault diagnosis [153][154][155][156][157][158] Dynamic modeling [159] Transient stability enhancement [160,161] Sensitivity analysis [162] Wind turbine flicker calculation [163] 4.1. Forecasting and prediction 4.1.1.…”

“…Brahmi et al [140] used an ANN observer for a speed sensorless PMSG in wind energy conversion system. In this paper, the authors studied the sensorless maximum power point tracking of wind generation system.…”