Optimization by Genetic Algorithm of a Wind Energy System applied to a Dual-feed Generator

Authors

  • Mourad Guediri Laboratory of Electrical Engineering and Industrial Electronics L2EI, University of Jijel, Jijel, Algeria
  • Nabil Ikhlef Laboratory of Electrical Engineering and Industrial Electronics L2EI, University of Jijel, Jijel, Algeria
  • Hocine Bouchekhou Laboratory of Electrical Engineering and Industrial Electronics L2EI, University of Jijel, Jijel, Algeria
  • Abdelhafid Guediri Faculty of Technology, VTRS Laboratory, University of El Oued, El Oued, Algeria
  • Abdelkarim Guediri Faculty of Technology, VTRS Laboratory, University of El Oued, El Oued, Algeria
Volume: 14 | Issue: 5 | Pages: 16890-16896 | October 2024 | https://doi.org/10.48084/etasr.8122

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)

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References

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How to Cite

[1]
Guediri, M., Ikhlef, N., Bouchekhou, H., Guediri, A. and Guediri, A. 2024. Optimization by Genetic Algorithm of a Wind Energy System applied to a Dual-feed Generator. Engineering, Technology & Applied Science Research. 14, 5 (Oct. 2024), 16890–16896. DOI:https://doi.org/10.48084/etasr.8122.

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