NDLI: Speed control of sensorless induction generator by artificial neural network in wind energy conversion system

Content Provider	IET Digital Library
Author	Merabet, Adel Tanvir, Aman A. Beddek, Karim
Abstract	This study presents a new strategy for estimating the states (rotor flux and speed) and the load torque to implement a multivariable controller for a sensorless three-phase squirrel-cage induction machine in wind energy conversion systems. The multivariable control is carried out using input–output feedback law and its objective is to track profiles of the rotational speed and the rotor flux amplitude. The state estimation considerably improves the performance of rotor flux based model reference adaptive system in the variable speed region of operation. The technique uses Kalman filter as a rotor flux observer and an artificial neural network adaption mechanism to estimate the rotor speed. The state estimation requires only the measurements of the stator voltages and currents. The estimation method, for both states and torque, is not invasive as no mechanical sensors are needed. The wind energy conversion system and the proposed control-estimation techniques are simulated in Matlab/Simulink software platform and tested using the OPAL-RT real-time simulator (OP5600) to verify the accuracy of the proposed control-estimation method.
Starting Page	1597
Ending Page	1606
Page Count	10
ISSN	17521416
Volume Number	10
e-ISSN	17521424
Issue Number	Issue 10, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/10/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2016.0285
Journal	IET Renewable Power Generation
Publisher Date	2016-06-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acceleration Angular Velocity Control Artificial Neural Network Adaption Mechanism Asynchronous Generator Asynchronous Machine Control of Electric Power System Control-estimation Technique Current Measurement Feedback Input-output Feedback Law Kalman Filter Load Torque MATLAB-Simulink Software Platform Mechanical Sensor Model Reference Adaptive Control System Multivariable Control System Multivariable Controller Neurocontrol Neurocontrollers Observers OP5600 OPAL-RT Real-time Simulator Power Generation Control Power System Control Power System State Estimation Rotation Control Rotor Flux Amplitude Rotor Flux Based Model Reference Adaptive System Rotor Flux Observer Rotor Speed Estimation Rotors Self Adjusting Control System Sensorless Induction Generator Sensorless Machine Control Sensorless Three-phase Squirrel-cage Induction Machine Speed Control State Estimation Stator Voltage Measurement Stators Variable Speed Region Velocity Wind Energy Conversion System Wind Power Plant
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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