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Artificial Intelligence Based on Particle Swarm Optimization for Optimal Wind Turbine Power Control Using Doubly Fed Induction Generator

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AI and IoT for Sustainable Development in Emerging Countries

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 105))

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Abstract

The system under investigation is a wind turbine of 5 MW connected via a gearbox to a doubly-fed induction generator (DFIG). The stator of this DFIG is connected directly to the grid, while the rotor uses back-to-back converters to connect to the grid. This chapter focuses on controlling the active and reactivepower generated by a variable wind power plant and the power transferred between the electrical grid and the system. A maximum power point tracking (MPPT) technique is also utilized to get the maximum power of the fluctuating wind speed. The rotor side converter (RSC) and grid side converter (GSC) decoupled vector control is principally established by a traditional Proportional-Integral (PI) and with an intelligent PI whose parameters are modified using the particle swarm optimization technique (PSO). Through Matlab/Simulink, the performances and results obtained by classical PI are studied and compared to those obtained by PSO tuned PI controller.

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Author information

Authors and Affiliations

  1. Laboratory: Electronics, Instrumentation and Energy – Team: Exploitation and Processing of Renewable Energy – Department of Physics, Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

    Elmostafa Chetouani, Youssef Errami, Abdellatif Obbadi & Smail Sahnoun

Authors
  1. Elmostafa Chetouani
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  2. Youssef Errami
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  3. Abdellatif Obbadi
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  4. Smail Sahnoun
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Editor information

Editors and Affiliations

  1. LIM, Hassan II University, Mohammedia, Morocco

    Zakaria Boulouard

  2. Moulay Ismail University, Meknes, Morocco

    Mariya Ouaissa

  3. Moulay Ismail University, Meknes, Morocco

    Mariyam Ouaissa

  4. Sidi Mohamed Ben Abdellah University, Fes, Morocco

    Sarah El Himer

Appendix

Appendix

See Tables 1, 2, 3 and 4.

Table 1 PI controller gains computed by pole compensation and by PSO methods
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Table 2 PI controller gains computed by pole compensation and by PSO methods
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Table 3 Set of parameters used for establishing the PSO algorithm
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Table 4 Set of parameters of the WECS utilized for the simulation
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Chetouani, E., Errami, Y., Obbadi, A., Sahnoun, S. (2022). Artificial Intelligence Based on Particle Swarm Optimization for Optimal Wind Turbine Power Control Using Doubly Fed Induction Generator. In: Boulouard, Z., Ouaissa, M., Ouaissa, M., El Himer, S. (eds) AI and IoT for Sustainable Development in Emerging Countries. Lecture Notes on Data Engineering and Communications Technologies, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-030-90618-4_8

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