Paper Info
Title
A robust wind turbine control using a Neural Network based wind speed estimator.
Abstract
Modern wind turbines are capable to work in variable speed operations. These wind turbines are provided with adjustable speed generators, like the double feed induction generator. One of the main advantage of adjustable speed generators is that they improve the system efficiency compared to fixed speed generators because turbine speed is adjusted as a function of wind speed to maximize output power. In this sense, to implement maximum wind power extraction, most controller designs of the variable-speed wind turbine generators employ anemometers to measure wind speed in order to obtain the desired optimal generator speed. In this paper a Neural Network based wind speed estimator for a wind turbine control is proposed. The design uses a feedforward Artificial Neural Network (ANN) to implement a wind speed estimator.In this work, a sliding mode control for variable speed wind turbines is also proposed. The stability analysis of the proposed controller is provided under disturbances and parameter uncertainties by using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed control scheme using an ANN estimator provides high-performance dynamic characteristics, and on the other hand that this scheme is robust under uncertainties that usually appear in the real systems and under wind speed variations.
Year
DOI
Venue
2010
10.1109/IJCNN.2010.5596859
IJCNN
Keywords
Field
DocType
Lyapunov methods,asynchronous generators,control system synthesis,feedforward neural nets,neurocontrollers,power generation control,robust control,wind turbines,Lyapunov stability theory,adjustable speed generators,controller designs,double feed induction generator,feedforward artificial neural network,maximum wind power extraction,neural network based wind speed estimator,robust wind turbine control,variable-speed wind turbine generators
Control theory,Wind speed,Computer science,Control theory,Anemometer,Turbine,Robust control,Induction generator,Wind power,Sliding mode control
Conference
ISSN
Citations 
PageRank 
1098-7576
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Oscar Barambones15613.24