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Integrated Intelligent Control and Fault System for Wind Generators



The goal of this paper is to show the possibility of combining fault detection analysis, detection, modeling, and control of the doubly-fed induction generator (DFIG) wind turbine using intelligent control and diagnostic techniques. To enable online detection of problems inside the power electronics converter we apply the wave direct analysis method which enables a complete model for fault detection that includes the power electronic stage itself. A neural network system based on Hebbian networks is applied for fault classification with good detection results in simulation. For controlling the wind turbine a number different artificial intelligence techniques are presented including fuzzy logic and an adaptive fuzzy inference systems (ANFIS) which combines the characteristics of fuzzy logic and neural networks. A Grey predictor is also integrated in the control scheme for predicting the wind profile. The combined fault detection and control scheme are validated using simulation results. The software development and control platform is LabVIEW which is one of the most powerful tools for simulating and implementing industrial control systems.



Total Pages: 17
Pages: 373-389


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Volume: 19
Issue: 3
Year: 2013

Cite this document


Fernando, D. Bianchi, et al. Wind turbine control systems. London: Springer-Verlag

Munteanu I. Optimal control of wind energy systems

Wind Generator model in LabVIEW internal report

Holdsworth L. IEE Proceedings: Generation, Transmission, Distribution

Karimi-Davijani H. World Applied Sciences Journal 6.4 (2009)

Vas P. Sensorless vector and direct torque control

Bose B. K. Modern power electronics and AC drives

Salman, S. K. & Badrzadeh, Babak (2005). New approach for modelling doubly-fed induction generator (DFIG) for grid-connection studies. School of Engineering, The Robert Gordon University. Presented at the International Conference on Power Systems Transients (IPST”05) in Montreal, Canada on June 19–23

Biswas, Agnimitra, & Gupta, R. (2009). An artificial neural network based methodology for the prediction of power & torque coefficients of a two bladed airfoil shaped H-rotor. Open Renewable Energy Journal, 2, 43

Gagnon, Richard, Sybille, Gilbert, Bernard, Serge, Paré, Daniel, Casoria, Silvano, & Larose, Christian. (2005). Modeling and real-time simulation of a doubly-fed induction generator driven by a wind turbine. Presented at the International Conference on Power Systems Transients (IPST”05) in Montreal, Canada on June 19–23. Available at:

Ekanayake Janaka B. IEEE Transactions on Power Systems 18.2 (2003)

Ponce-Cruz, Pedro, and Fernando D. Ramírez-Figueroa. "Intelligent Control Systems with LabVIEW™." (2010): n. pag. Crossref. Web.

Manual control & simulation toolkit (LabVIEW)

Bohlin T. International Journal of Adaptive Control and Signal Processing

Holst J. Selected papers from the fourth IFAC symposium on adaptive systems in control and signal processing

Jang J.-S. R. The Proceedings of the IEEE

Jang J.-S. R. IEEE Trans. on Systems, Man, and Cybernetics

Zhe, Wang, & Qingding, Guo. (2007). The diagnosis method for converter fault of the variable SpeedWindTurbine based on the neural networks, IEEE

Hao Ma Dianli Dianzi Jishu

Merryman Stephen A. IEEE Trans. on Industrial Electronics 42.6 (1995)

Shuyan Fang Technological Development of Enterprise 24.8 (2005)


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


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