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Sedaghati, Reza
- A Novel Control Strategy Study for DFIG-based Wind Turbine
Abstract Views :498 |
PDF Views:124
Authors
Affiliations
1 Young Researchers Club, Beyza Branch, Islamic Azad University, Beyza, IR
1 Young Researchers Club, Beyza Branch, Islamic Azad University, Beyza, IR
Source
Indian Journal of Science and Technology, Vol 5, No 12 (2012), Pagination: 3741-3745Abstract
In recent years the use of renewable energy including wind energy has risen dramatically. Because of the increasing development of wind power production, improvement of the control of wind turbines using classical or intelligent methods is necessary. In this paper, in order to control the power of wind turbine equipped with DFIG, a novel intelligent controller based on the human mind's emotional learning is designed. The performance of proposed controller is confirmed by simulation results. Some outstanding properties of this new controller are online implementation capability, structural simplicity and its robustness against any changes in wind speed and system parameters variations.Keywords
Double Fed Induction Generator(DFIG), Emotional Learning, Wind Turbine, Intelligent ControllerReferences
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- Tapia, G., Tapia, A. and Ostolaza, J. X., (2006) Two Alternative Modeling Approaches for the Evaluation of Wind Farm Active and Reactive Power Performances, IEEE Trans. on Energy Conversion, Vol. 21, pp. 909-920.
- Hand, M. M. and Balas, M. J., (1998) Systematic Approach for PID Controller Design for Pitch-Regulated, Variable-Speed Wind Turbines, 17th ASME Wind Energy Symposium Proceedings, pp. 89–94.
- Beltran, B., Ahmed-Ali, T. and Benbouzid, M. E., (2008) Sliding Mode Power Control of Variable-Speed Wind Energy Conversion Systems, IEEE Trans. on Energy Conversion, June.
- Utkin, V. I., “Sliding Mode Control Design Principles and Applications to Electric drives, (1993) IEEE Trans. on Industrial Electronics., Vol. 40, pp. 23–36.
- Lascu, C., Boldea, I. and Blaabjerg, F., (2004) Direct Torque Control of Sensorless Induction Motor Drives: a Sliding- Mode Approach,” IEEE Trans. on Industrial Applications, Vol. 40, pp.582–590.
- Zhang, X.-Y., Cheng. J. and Wang, W.-Q., (2008) The Intelligent Control Method Study of Variable Speed Wind Turbine Generator, ICSET.
- Jerbi, L., Krichen, L. and Ouali, A., (2009) A Fuzzy Logic Supervisor for Active and Reactive Power Control of a Variable Speed Wind Energy Conversion System Associated to a Flywheel Storage System, Electric Power Systems Research, Vol. 79, pp. 919–925.
- B. Boukhezzar and H. Siguerdidjane, (2009) Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization, Energy Conversion and Management, vol. 50, pp. 885–892.
- L. Fan, H. Yin and Z. Miao, (2011) A novel control scheme for DFIG-based wind energy systems under unbalanced grid conditions, Electric Power Systems Research, vol. 81, pp. 254–262.
- H. Nian and H. Xuh, (2011) Dynamic modeling and improved control of DFIG under distorted grid voltage conditions, IEEE Transaction on Power System, vol. 26, no. 1, pp.163–175.
- Ion. Boldea, (2006) A The Electric Generators Handbook VARIABLE SPEED GENERATORS, J. CRC Press, the United State of America.
- J. Moren, and Balkenius, (2000) A Computational Model of Emotional Learning in the Amygdala, from animals to animals 6: Proc. of the 6th International Conference on the Simulation of Adaptive Behaviour, Cambridge, Mass., (the MIT Press).
- Enhancement of Power System Dynamic Performance Using Coordinated Control of Facts Devices
Abstract Views :218 |
PDF Views:0
Authors
Affiliations
1 Young Researchers and Elite Club, Beyza Branch, Islamic Azad University, Beyza, IR
2 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, IR
1 Young Researchers and Elite Club, Beyza Branch, Islamic Azad University, Beyza, IR
2 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, IR
Source
Indian Journal of Science and Technology, Vol 7, No 10 (2014), Pagination: 1513-1524Abstract
To improve transient stability and enhancement of the power system oscillations damping, this paper proposes a specific structure of coordination between FACTS devices based on TCSC and SVC. In order to improve the performance and use all the features of TCSC and SVC, it is necessary to use controllers especially intelligent controller in which the ADALINE neural network is one of them. The designed combination for FACTS Devices is according to a current injection model and therefore, it is possible to use a fixed admittance matrix in the calculations. To understand the performance of the ADALINE neural network controller better, it was compared with a controller designed by the optimal control parameters of Linear Quadratic Regulator (LQR). The power system transient simulation results on a Single-Machine Infinite-Bus (SMIB) system has shown that the ADALINE neural network controller has better performance than the LQR controller and can cause significant improvement on damping oscillations and power transmission ability in the electrical system.Keywords
ADALINE Neural Network, Current Injection Models, Damping Oscillations, Power System Dynamics, SVC, TCSC.- A Novel Fuzzy-based Power System Stabilizer for Damping Power System Enhancement
Abstract Views :285 |
PDF Views:0
Authors
Affiliations
1 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, IR
1 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, IR