Fuzzy PI Control Strategy to Doubly Fed Induction Wind Turbine for Power Maximization in Presence of Disturbances

Main Article Content

Eduardo Muñoz
Edy Ayala
Nicolás Pozo

Abstract

This research proposes a control methodology applied to a Wind Power Generation Systems (WEGS) for Maximum Power Point Tracking (MPPT) technique based on a Fuzzy observer and complemented by a PI controller using the Direct Speed Control (DSC) method. This approach permits commanding the rotor side reference current  through the variations of torque and electrical power in a Doubly Fed Induction Generator (DFIG) model. Consequently, the speed of the generator is controlled in order to obtain a rapid response of the maximum Power Coefficient (). The construction of this strategy starts with direct measurements of the electrical and mechanical variables using computational tools such as FAST and Matlab-Simulink for the wind turbine model simulations. This DSC strategy presents a rapid performance of the  tracking considering the dynamics of a 1.5MW wind turbine and this strategy has been compared to a traditional PI controller improving the extraction of the output power.

Downloads

Download data is not yet available.

Article Details

How to Cite
Muñoz , E., Ayala, E., & Pozo, N. (2021). Fuzzy PI Control Strategy to Doubly Fed Induction Wind Turbine for Power Maximization in Presence of Disturbances. Revista Técnica "energía", 18(1), PP. 1–10. https://doi.org/10.37116/revistaenergia.v17.n2.2021.428
Section
SISTEMAS ELÉCTRICOS DE POTENCIA

References

[1] M. M. Rezaei, "A nonlinear maximum power point tracking technique for DFIG-based wind energy conversion systems," Engineering Science and Technology, an International Journal, vol. 21, no. 5, pp. 901-908, July 2018.
[2] E. Ayala and S. Simani, "Perturb and observe maximum power point tracking algorithm for permanent magnet synchronous generator wind turbine systems", in 15th European Workshop on Advanced Control and Diagnosis – ACD 2019 (G. Conte, Ed.). Lecture Notes in Control and Information Sciences. Proceedings, Alma Mater Studiorum, University of Bologna. Springer. Bologna, Italy. pp. 1–11, 2019.
[3] B. Boukhezzar and H. Siguerdidjane, "Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization," Energy Conversion and Management, vol. 50, no. 4, pp. 885-892, 2009.
[4] A. Ben Amar, S. Belkacem and T. Mahni, "Direct torque control of a doubly fed induction generator," International Journal of Energetica (IJECA), vol. 2, no. 1, pp. 11-14, 2017.
[5] A. Bakouri, A. A. Hassan Mahmoudi and K. Elyaalaoui, "Direct Torque Control of a Doubly Fed Induction Generator of Wind Turbine for Maximum Power Extraction," in 2014 International Renewable and Sustainable Energy Conference (IRSEC), Ouarzazate, 2014.
[6] Y. Sahri, S. Tamalouzt and S. L. Belaid, "Direct Torque Control of DFIG Driven by Wind Turbine System Connected to the Grid," in 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA), Algiers, 2018.
[7] A. Bakouri, H. Mahmoudi, A. Abbou and M. Moutchou, "Optimizing the wind power capture by using DTC technique based on Artificial Neural Network for a DFIG variable speed wind turbine," in 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA), Rabat, 2015.
[8] J. Singh Thongam y M. Ouhrouche, "MPPT Control Methods in Wind Energy, " de Fundamental and Advanced Topics in Wind Power, Dr. Rupp Carriveau, Ed., InTech, 2011, pp. 339-360.
[9] V. Calderaro, V. Galdi, A. Piccolo and P. Siano, "A fuzzy controller for maximum energy extraction from variable speed wind power generation systems," Electric Power Systems Research, vol. 78, no. 6, pp. 1109-1118, 2008.
[10] M. El Azzaoui y H. Mahmoudi, "Fuzzy-PI control of a doubly fed induction generator-based wind power system," International Journal of Automation and Control, vol. 11, no. 1, pp. 54-66, 2017.
[11] C. Fu, T. Pan, H. Liu, D. Wu, Y. Shen y Z. Hao, "MPPT Control Based Fuzzy for Wind Energy Generating System, " de 2018 37th Chinese Control Conference (CCC), Wuhan, 2018.
[12] A. Meharrar, M. Tioursi, M. Hatti and A. Boudghène Stambouli, "A variable speed wind generator maximum power tracking based on adaptative neuro-fuzzy inference system," Expert Systems with Applications, vol. 38, no. 6, pp. 7659-7664, 2011.
[13] G. Hou, Z. Jiang, Y. Yang and J. Zhang, "Variable universe fuzzy controller used in MPPT based on DFIG wind energy conversion system," in 2016 Chinese Control and Decision Conference (CCDC), Yinchuan, 2016.
[14] M. Sheikhan, R. Shahnazi and A. Nooshad Y., "An optimal fuzzy PI controller to capture the maximum power for variable-speed wind turbines," Neural Comput & Applic, vol. 23, no. 5, pp. 1359–1368, 2013.
[15] F. E. Tahiri, K. Chikh and M. Khafallah, "MPPT strategy using Fuzzy-PI controller applied to a standalone wind energy conversion system," in SCA '18: Proceedings of the 3rd International Conference on Smart City Applications, Tetouan, 2018.
[16] S. Karad and R. Thakur, "Recent Trends of Control Strategies for Doubly Fed Induction Generator Based Wind Turbine Systems: A Comparative Review," Archives of Computational Methods in Engineering, pp. 1-15, 2019.
[17] National Renewable Energy Laboratory (NREL). Available: https://www.nrel.gov/. [Last access: 2020].
[18] MATLAB, 2018, 9.5.0.944444 (R2018b), The MathWorks Inc., Natick, Massachusetts.
[19] F. Baldo, "Modeling of Load Interfaces for a Drive Train of a Wind Turbine," Master's Thesis, Department of Applied Mechanics, Chalmers University of Technology, Gothenburg, 2012.
[20] M. Abdullah, A. Yatim, C. Tan and R. Saidur, "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, vol. 16, no. 5, pp. 3220-3227, 2012.
[21] B. Boukhezzar and H. Siguerdidjane, "Nonlinear Control of a Variable-Speed Wind Turbine Using a Two-Mass Model," IEEE Transactions on Energy Conversion, vol. 26, no. 1, pp. 149-162, March 2011.
[22] M. Narayana, G. Putrus, M. Jovanovic, P. Leung and S. McDonald, "Generic maximum power point tracking controller for small-scale wind turbines," Renewable Energy, vol. 44, pp. 72-79, 2012.
[23] O. Uluyol, G. Parthasarathy, W. Foslien and K. Kim, "Power Curve Analytic for Wind Turbine Performance Monitoring and Prognostics," in Annual Conference of the Prognostics and Health Management Society, Montreal, 2011.
[24] G. Michalke, "Variable Speed Wind Turbines - Modelling, Control, and Impact on Power Systems," PhD thesis (Dr.-Ing.), Electrical and Computer Engineering, Technical University of Darmstadt, Darmstadt, 2008.
[25] G. Semrau, S. Rimkus and T. Das, "Nonlinear Systems Analysis and Control of Variable Speed Wind Turbines for Multiregime Operation," Journal of Dynamic Systems, Measurement, and Control, vol. 137, no. 4, pp. 1-10, April 2015.
[26] P. O. Ohiero, "Development of Fast Multi-System Simulation Models for Permanent Magnet Synchronous Motor and Generator Drive Systems," PhD thesis, School of Engineering, College of Science and Engineering, University of Glasgow Glasgow, July 2015.
[27] O. P. Bharti, R. K. Saket and S. K. Nagar, "Design of PI controller for doubly fed induction generator using static output feedback," in 2015 39th National Systems Conference (NSC), Noida, 2015.
[28] B. Rached, M. Elharoussi, and E. Abdelmounim, "Design and investigations of MPPT strategies for a wind energy conversion system based on doubly fed induction generator," International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 5, p. 4770~4781, October 2020.
[29] K. Ouezgan, B. Bossoufi and M. N. Bargach, "DTC Control of DFIG-Generators for Wind Turbines: FPGA Implementation Based," in 2017 International Renewable and Sustainable Energy Conference (IRSEC), Tangier, 2017.
[30] H. Abu-Rub, M. Malinowski and K. Al-Haddad, "Properties and Control of a Doubly Fed Induction Machine," in Power Electronics for Renewable Energy Systems, Transportation and Industrial Applications, Chennai, WILEY, 2014, pp. 280-284.
[31] G. Abad, J. López, M. A. Rodríguez, L. Marroyo and G. Iwanski, DOUBLY FED INDUCTION MACHINE, MODELING AND CONTROL FOR WIND ENERGY GENERATION, New Jersey: WILEY, 2011.
[32] R. M. Hilloowala and A. M. Sharaf, "A rule-based fuzzy logic controller for a PWM inverter in a stand alone wind energy conversion scheme," IEEE Transactions on Industry Applications, vol. 32, no. 1, pp. 57-65, Jan.-Feb. 1996.
[33] J. M. Jonkman and M. L. Buhl Jr., "FAST User’s Guide," NREL/EL-500-38230. Golden, Colorado: National Renewable Energy Laboratory 2005.