Optimization by Genetic Algorithm of a Wind Energy System applied to a Dual-feed Generator
Received: 13 June 2024 | Revised: 12 July 2024 | Accepted: 16 July 2024 | Online: 24 August 2024
Corresponding author: Mourad Guediri
Abstract
In an attempt to improve wind energy production using a Doubly Fed Induction Generator (DFIG), this paper presents a model for power maximization through controlling the turbine speed by utilizing a Maximum Peak Power Tracking (MPPT) controller, and through also controlling the stator active and reactive power for DFIG. In the context of increasing the search for new electric energy production sources, including renewable energies, Proportional Integral (PI) contributed to the modeling of the control and improvement of the wind energy conversion system, with the aim of exploiting wind energy to produce clean energy without pollution. To enhance the benefits of classic PI regulators, and so obtain efficient performance, the study seeks to determine the parameters of PI regulators. PI is used for wind turbines without including classical analytical methods for final calculation. Thus, optimization algorithms, namely Genetic Algorithms (GA) or Particle Swarm Optimization (PSO), which seek to minimize the error in a controlled system between the input signal and the output signal, were developed in this study. The basis of this approach is the management of both reactive and active power. In order to increase performance and efficiency, the new approach incorporates GA ideas into the control technology used in the wind turbine. The simulation results derived after this incorporation provide wind turbine systems that are more stable and efficient producing significantly better results than traditional PI regulators. Then, a simulation program, which includes the artificial intelligence controls and GA, is created in Matlab.
Keywords:
Doubly Fed Induction Generator (DFIG), Maximum Peak Power Tracking (MPPT), Proportional Integral (PI), maximizaton of wind power production, Hybrid Genetic Algorithm (HGA)Downloads
References
REFERENCES
L. Pan, Z. Zhu, Y. Xiong, and J. Shao, "Integral Sliding Mode Control for Maximum Power Point Tracking in DFIG Based Floating Offshore Wind Turbine and Power to Gas," Processes, vol. 9, no. 6, Jun. 2021, Art. no. 1016.
Y. Dbaghi, S. Farhat, M. Mediouni, H. Essakhi, and A. Elmoudden, "Indirect power control of DFIG based on wind turbine operating in MPPT using backstepping approach," International Journal of Electrical and Computer Engineering (IJECE), vol. 11, no. 3, pp. 1951–1961, Jun. 2021.
U. Yilmaz, A. Kircay, and S. Borekci, "PV system fuzzy logic MPPT method and PI control as a charge controller," Renewable and Sustainable Energy Reviews, vol. 81, pp. 994–1001, Jan. 2018.
S. S. G, A. E. X. S, and R. VR, "Fatigue load mitigation in wind turbine using a novel anticipatory predictive control strategy," Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 234, no. 1, pp. 60–80, Jan. 2020.
M. Benmeziane, S. Zebirate, A. Chaker, and Z. Boudjema, "Fuzzy sliding mode control of doubly-fed induction generator driven by wind turbine," International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 10, no. 3, pp. 1592–1602, Sep. 2019.
H. A. Aroussi, E. Ziani, M. Bouderbala, and B. Bossoufi, "Improvement of direct torque control applied to doubly fed induction motor under variable speed," International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 11, no. 1, pp. 97–106, Mar. 2020.
T. Mebkhouta, A. Golea, R. Boumaraf, T. M. Benchouia, and D. Karboua, "A High Robust Optimal Nonlinear Control with MPPT Speed for Wind Energy Conversion System (WECS) Based on Doubly Fed Induction Generator (DFIG)," Periodica Polytechnica Electrical Engineering and Computer Science, vol. 68, no. 1, pp. 1–11, 2024.
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 (IJEEI), vol. 7, no. 2, pp. 165–181, May 2019.
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.
J. O. Spiegel and J. D. Durrant, "AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization," Journal of Cheminformatics, vol. 12, no. 1, Apr. 2020, Art. no. 25.
A. Guediri and S. Touil, "Optimization Using a Genetic Algorithm Based on DFIG Power Supply for the Electrical Grid," International Journal of Engineering, vol. 35, no. 1, pp. 121–129, Jan. 2022.
S. Kharoubi and L. E. Menzhi, "Wind turbine doubly-fed induction generator defects diagnosis using rotor currents lissajous curves," International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 11, no. 4, pp. 2083–2090, Dec. 2020.
A. Tan, Z. Tang, X. Sun, J. Zhong, H. Liao, and H. Fang, "Genetic Algorithm-Based Analysis of the Effects of an Additional Damping Controller for a Doubly Fed Induction Generator," Journal of Electrical Engineering & Technology, vol. 15, no. 4, pp. 1585–1593, Jul. 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.
Z. Zeghdi, L. Barazane, Y. Bekakra, and A. Larabi, "Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm," Periodica Polytechnica Electrical Engineering and Computer Science, vol. 66, no. 1, pp. 43–59, Jan. 2022.
B. Kelkoul and A. Boumediene, "Stability analysis and study between classical sliding mode control (SMC) and super twisting algorithm (STA) for doubly fed induction generator (DFIG) under wind turbine," Energy, vol. 214, Jan. 2021, Art. no. 118871.
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.
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Copyright (c) 2024 Mourad Guediri, Nabil Ikhlef, Hocine Bouchekhou, Abdelhafid Guediri, Abdelkarim Guediri
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