Abstract
This paper suggested a methodology for controlling a wind turbine, which is branched to a doubly-fed induction generator (DFIG) via a gearbox. The DFIG stator is immediately connected to the power system, whereas the rotor is linked to the grid through the AC/DC/AC converters. The objective is to manage the powers extracted from a fluctuating wind turbine system. A maximum power point tracking (MPPT) technique is also employed to acquire the highest power of the fluctuating wind speed. The control of the rotor side converter based on stator field-oriented vector is designed using a traditional Proportional-Integral (PI) and with a smart PI whose gains are optimized using the particle swarm optimization approach. The integral square error (ISE) is used as a cost function to minimize the error. Through Matlab/Simulink, the performances and outcomes achieved by classical PI are studied and compared to those obtained by PSO tuned PI controller. The PSO ensures the tracking system’s stability and reduces response time to 1.7 (ms) with a neglected static error.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S.: Optimal tuning of PI controllers using adaptive particle swarm optimization for doubly-fed induction generator connected to the grid during a voltage dip. Bull. Electr. Eng. Inform. 10(5), 2367–2376 (2021)
Bellarbi, S.: Electromechanical study the wind energy conversion system based DFIG and SCIG generators. Int. J. Mech. 15(11), 102 (2021)
Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S.: Design of optimal backstepping control for a wind power plant system using the adaptive weighted particle swarm optimization. Int. J. Intell. Eng. Syst. 14(6), 125–136 (2021)
Chojaa, H., Derouich, A., Taoussi, M., Zamzoum, O., Hanafi, A.: An improved performance variable speed wind turbine driving a doubly fed induction generator using sliding mode strategy. In: IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science, pp. 1–8. IEEE, Kenitra, Morocco (2020)
Rafiee, Z., Rafiee, M., Aghamohammadi, M.: An investigation of the influences of the voltage sag on the doubly fed induction generator using tuned PI controllers. Tehnički vjesnik 27(1), 149–156 (2020)
Rached, B., Elharoussi, M., Abdelmounim, E.: Fuzzy logic control for wind energy conversion system based on DFIG. In: 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS), pp. 1–6, Fez, Morocco (2019)
Rahmanifard, H., Plaksina, T.: Application of artificial intelligence techniques in the petroleum industry: a review. Artif. Intell. Rev. 52(4), 2295–2318 (2018). https://doi.org/10.1007/s10462-018-9612-8
Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S.: Maximum power point tracking design using particle swarm optimization algorithm for wind energy conversion system connected to the grid. In: Renewable Energy Systems, pp. 445–470 (2021)
Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S.: Backstepping and indirect vector control for rotor side converter of doubly fed-induction generator with maximum power point tracking. In: Motahhir, S., Bossoufi, B. (eds.) ICDTA 2021. LNNS, vol. 211, pp. 1711–1723. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73882-2_155
Taoussi, M., et al.: Low-speed sensorless control for wind turbine system. WSEAS Trans. Syst. Control 12, 405–417 (2017)
Dai, H., Chen, D., Zheng, Z.: Effects of random values for particle swarm optimization algorithm. Algorithms 11(2), 23 (2018)
Bekakra, Y., Attous, D.B.: Optimal tuning of PI controller using PSO optimization for indirect power control for DFIG based wind turbine with MPPT. Int. J. Syst. Assur. Eng. Manag. 5(3), 219–229 (2013). https://doi.org/10.1007/s13198-013-0150-0
Kumar, A., Gupta, R.: Compare the results of tuning of PID controller by using PSO and GA technique for AVR system. Int. J. Adv. Res. Comput. Eng. Technol. (IJARCET) 2(6), 1–9 (2013)
Taoussi, M., Karim, M., Hammoumi, D., Bekkali, C.E., Bossoufi, B., Ouanjli, N.E.: Comparative study between backstepping adaptive and field-oriented control of the DFIG applied to wind turbines. In: 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp. 1–6. IEEE, Fez, Morocco (2017)
Demirbas, S.: Self-tuning fuzzy-PI-based current control algorithm for doubly fed induction generator. IET Renew. Power Gener. 11(13), 1714–1722 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S., Chojaa, H. (2022). Optimization Power Control for Rotor Side Converter of a DFIG Using PSO Evolutionary Algorithm. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-031-02447-4_56
Download citation
DOI: https://doi.org/10.1007/978-3-031-02447-4_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-02446-7
Online ISBN: 978-3-031-02447-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)