Control of a Doubly Fed Induction Generator for Variable Speed Wind Energy Conversion Systems using Fuzzy Controllers optimized with a Genetic Algorithm
Received: 31 October 2024 | Revised: 28 November 2024 | Accepted: 1 December 2024 | Online: 20 December 2024
Corresponding author: Mourad Guediri
Abstract
This paper presents a comprehensive study of a wind turbine system operating under variable wind conditions, utilizing a Doubly Fed Induction Generator (DFIG) connected to the grid. The DFIG is controlled via a rotor-side transducer, allowing for independent regulation of the conductors to manage both active and reactive power flows effectively. The control strategy focuses on generating reference voltages for the rotor to ensure that active and reactive power align with the desired targets, optimizing the tracking of the maximum power point to maximize electrical output. The research analyzes the system's dynamic performance under fluctuating wind conditions, emphasizing control strategies for managing active and reactive energy. A notable innovation is the integration of fuzzy logic and genetic algorithm into the control strategy for the wind turbine's switching mechanism, which enhances system performance and efficiency. Simulation results demonstrate that this approach provides higher efficiency, improved performance, and greater stability compared to the traditional Proportional-Integral (PI) controllers. Advanced artificial intelligence methods, such as fuzzy genetic algorithm control, were employed and the proposed system's effectiveness was validated with Matlab/Simulink simulations.
Keywords:
Doubly Fed Induction Generator (DFIG), hybrid genetic algorithms, electrical network, fuzzy controller, Fuzzy Genetic Algorithm (FGA)Downloads
References
S. Abderrahim, M. Allouche, and M. Chaabane, "Power optimisation of wind energy conversion system using T-S fuzzy approach," International Journal of Industrial and Systems Engineering, vol. 38, no. 1, pp. 35–58, Jan. 2021.
S. A. E. M. Ardjoun and M. Abid, "Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines," Turkish Journal of Electrical Engineering and Computer Sciences, vol. 23, no. 6, pp. 1673–1686, Jan. 2015.
S. Massoum, A. Meroufel, A. Massoum, and P. Wira, "A direct power control of the doubly-fed induction generator based on the SVM Strategy," Elektrotehniski Vestnik, vol. 84, no. 5, pp. 235–240, Aug. 2017.
A. K. Guediri and D. Ben Attous, "Modeling and fuzzy control of a wind energy system based on double-fed asynchronous machine for supply of power to the electrical network," International Journal of System Assurance Engineering and Management, vol. 8, no. 1, pp. 353–360, Jan. 2017.
A. K. Guediri and D. Ben Attous, "Fuzzy control of a doubly fed asynchronous machine (DFAM) generator driven by a wind turbine modeling and simulation," International Journal of System Assurance Engineering and Management, vol. 8, no. 1, pp. 8–17, Jan. 2017.
S. Kouadria, Y. Messlem, and E. M. Berkouk, "Sliding mode control of the active and reactive power of DFIG for variable-speed wind energy conversion system," in 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), Marrakech, Morocco, Sep. 2015, pp. 1–8.
A. J. P. Delima, A. M. Sison, and R. P. Medina, "A modified genetic algorithm with a new crossover mating scheme," Indonesian Journal of Electrical Engineering and Informatics, vol. 7, no. 2, pp. 165–181, May 2019.
I. Kharchouf, T. Nasser, A. Essadki, and M. Fdaili, "Adaptive Fuzzy-PI Control of Wind Energy Conversion System Based DFIG Under Voltage Dip," in International Conference on Electrical and Information Technologies, Rabat, Morocco, Mar. 2020, pp. 1–6.
H. Elouatoua, T. Nasser, and A. Essadki, "Control of a Doubly-Fed Induction Generator for Wind Energy Conversion Systems," in International Conference on Electrical and Information Technologies, Rabat, Morocco, Mar. 2020, pp. 1–6.
A. Guediri, A. Guediri, and S. Touil, "A Genetic Algorithm Based on Optimization for Doubly Fed Induction Generator," International Journal of Engineering, Transactions A: Basics, vol. 35, no. 1, pp. 1–9, Jan. 2022.
K. A. Naik, C. P. Gupta, and E. Fernandez, "Performance improvement of a wind energy system using fuzzy logic based pitch angle control," Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 3, pp. 30–37, May 2018.
A. Guediri, A. Guediri, and S. Touil, "Modeling And Adaptive Fuzzy Logic Control Of A Wind Power System Based On DFIG For Power Supply To Electrical Grid," Turkish Journal of Computer and Mathematics Education, vol. 13, no. 03, pp. 882–994, Nov. 2022.
M. Guediri, N. Ikhlef, H. Bouchekhou, A. Guediri, and A. Guediri, "Optimization by Genetic Algorithm of a Wind Energy System applied to a Dual-feed Generator," Engineering, Technology & Applied Science Research, vol. 14, no. 5, pp. 16890–16896, Oct. 2024.
A. Benamor, M. T. Benchouia, K. Srairi, and M. E. H. Benbouzid, "A new rooted tree optimization algorithm for indirect power control of wind turbine based on a doubly-fed induction generator," ISA Transactions, vol. 88, pp. 296–306, May 2019.
H. Bakir, A. Merabet, R. K. Dhar, and A. A. Kulaksiz, "Bacteria foraging optimisation algorithm based optimal control for doubly-fed induction generator wind energy system," IET Renewable Power Generation, vol. 14, no. 11, pp. 1850–1859, 2020.
A. Radaideh, M. Bodoor, and A. Al-Quraan, "Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling," Journal of Electrical and Computer Engineering, vol. 2021, no. 1, 2021, Art. no. 1218236.
B. Belabbas, T. Allaoui, M. Tadjine, and M. Denai, "High Order Sliding Mode Controller Simulation by a Wind Turbine for DFIG Protection against Overcurrent.," Electrotehnica, Electronica, Automatica, vol. 65, no. 4, pp. 142-147, 2017.
M. Parvane, E. Rahimi, and F. Jafarinejad, "Optimization of Quantum Cellular Automata Circuits by Genetic Algorithm," International Journal of Engineering, vol. 33, no. 2, pp. 229–236, Feb. 2020.
A. Guediri, M. Hettiri, and A. Guediri, "Modeling of a Wind Power System Using the Genetic Algorithm Based on a Doubly Fed Induction Generator for the Supply of Power to the Electrical Grid," Processes, vol. 11, no. 3, Mar. 2023, Art. no. 952.
Downloads
How to Cite
License
Copyright (c) 2024 Mourad Guediri, Slimane Touil, Messaoud Hettiri, Abdelhafid Guediri, Nabil Ikhlef, Bouchekhou Hocine, Abdelkarim Guediri
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
