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Modeling and Lyapunov-designed based on Adaptive Gain Sliding Mode Control for wind turbines

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, modeling and the Lyapunov-designed control approach are studied for the Wind Energy Conversion Systems (WECS). The objective of this study is to ensure the maximum energy production of a WECS while reducing the mechanical stress on the shafts (turbine and generator). Furthermore, the proposed control strategy aims to optimize the wind energy captured by the wind turbine operating under rating wind speed, using an Adaptive Gain Sliding Mode Control (AG-SMC). The adaptation for the sliding gain and the torque estimation are carried out using the sliding surface as an improved solution that handles the conventional sliding mode control. Furthermore, the resultant WECS control policy is relatively simple, meaning the online computational cost and time are considerably reduced. Time-domain simulation studies are performed to discuss the effectiveness of the proposed control strategy.
Rocznik
Strony
124--136
Opis fizyczny
Bibliogr. 23 poz., rys., tab., wykr.
Twórcy
  • Electro-technical Engineering Lab, Faculty of Technology, Tahar Moulay University, 20 000 Saida, Algeria
autor
  • Electro-technical Engineering Lab, Faculty of Technology, Tahar Moulay University, 20 000 Saida, Algeria
  • Electro-technical Engineering Lab, Faculty of Technology, Tahar Moulay University, 20 000 Saida, Algeria
  • Electrical Energy LAB EELAB, Technologiepark 913 B 9052 Zwijnaarde, Ghent, Belgium
Bibliografia
  • [1] M. H. Baloch, J. Wang, G. S. Kaloi, (0043) modeling and controller design for wind energy conversion system based on a cage induction generator using turbulence speed, Journal of Power Technologies.
  • [2] T. Ackermann, Wind power in power systems, in JG. Slootweg, H. Polinder, W L. Kling, Reduced Order Modeling of Wind Turbines, New York, NY, USA: Wiley (2005) 555–585.
  • [3] J. Slootweg, H. Polinder, W. Kling, Reduced-order modelling of wind turbines, Wind power in power systems (2005) 555–585.
  • [4] K. Kerrouche, A. Mezouar, L. Boumedien, The suitable power control of wind energy conversion system based doubly fed induction generator, International Journal of Computer Applications 87 (3).
  • [5] O. Publishing, I. E. Agency, World energy out look. Paris: Organisation for Economic Cooperation and Development; 2010.
  • [6] E.W. E. Association, Wind directions-the European wind industry magazine 1 (1) (2012).
  • [7] A. Nadhir, T. Hiyama, Maximum power point tracking based optimal control wind energy conversion system, in: Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on, IEEE, 2010, pp. 41–44.
  • [8] K. Ghedamsi, D. Aouzellag, E. Berkouk, Control of wind generator associated to a flywheel energy storage system, Renewable Energy 33 (9) (2008) 2145–2156.
  • [9] F. Amrane, A. Chaiba, S. Mekhilef, High performances of gridconnected dfig based on direct power control with fixed switching frequency via mppt strategy using mrac and neuro-fuzzy control, Journal of Power Technologies 96 (1) (2016) 27–39.
  • [10] V. Calderaro, V. Galdi, A. Piccolo, P. Siano, A fuzzy controller for maximum energy extraction from variable speed wind power generation systems, Electric Power Systems Research 78 (6) (2008) 1109–1118.
  • [11] V. Galdi, A. Piccolo, P. Siano, Exploiting maximum energy from variable speed wind power generation systems by using an adaptive takagi–sugeno–kang fuzzy model, Energy Conversion and Management 50 (2) (2009) 413–421.
  • [12] F. Poitiers, T. Bouaouiche, M. Machmoum, Advanced control of a doubly-fed induction generator for wind energy conversion, Electric Power Systems Research 79 (7) (2009) 1085–1096.
  • [13] A. Kerboua, Hybrid fuzzy sliding mode control of a doubly-fed induction generator speed in wind turbines, Journal of Power Technologies 95 (2) (2015) 126.
  • [14] K. D.-E. Kerrouche, A. Mezouar, L. Boumediene, K. Belgacem, Modeling and optimum power control based dfig wind energy conversion system, International Review of Electrical Engineering (IREE) 9 (1) (2014) 174–185.
  • [15] I. Munteanu, A. I. Bratcu, N.-A. Cutululis, E. Ceanga, Optimal control of wind energy systems: towards a global approach, Springer Science & Business Media, 2008.
  • [16] A. Manjock, Design codes fast and adams for load calculations of onshore wind turbines, 2005, National Renewable Energy Laboratory (NREL): Golden, Colorado, USA.
  • [17] M. Stiebler, Wind energy systems for electric power generation, Springer Science & Business Media, 2008.
  • [18] A. Petersson, T. Thiringer, L. Harnefors, T. Petru, Modeling and experimental verification of grid interaction of a dfig wind turbine, Energy Conversion, IEEE Transactions on 20 (4) (2005) 878–886.
  • [19] S. Abdeddaim, A. Betka, Optimal tracking and robust power control of the dfig wind turbine, International Journal of Electrical Power & Energy Systems 49 (2013) 234–242.
  • [20] K. Kerrouche, A. Mezouar, L. Boumedien, A simple and efficient maximized power control of dfig variable speed wind turbine, in: Systems and Control (ICSC), 2013 3rd International Conference on, IEEE, 2013, pp. 894–899.
  • [21] V. I. Utkin, Sliding Modes in Optimization and Control. New York: Springer-Verlag, 1992.
  • [22] F. Plestan, Y. Shtessel, V. Bregeault, A. Poznyak, New methodologies for adaptive sliding mode control, International journal of control 83 (9) (2010) 1907–1919.
  • [23] K. Ouari, T. Rekioua, M. Ouhrouche, Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer, ISA transactions 53 (1) (2014) 76–84.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b8dcc774-cbc3-4340-82af-16fa0d4aaedc
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