Optimal pitch angle controller for DFIG-based wind turbine system using computational optimization techniques

Arsalan Khurshid, Muhammad Ali Mughal, Achraf Othman, Tawfik Al-Hadhrami, Harish Kumar, Imtinan Khurshid, Arshad*, Jawad Ahmad

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
8 Downloads (Pure)


With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum wind power in a wind turbine system (WTS). The pitch angle controller contributes to improve the output power at different wind speeds. In this paper, the pitch angle controller with proportional (P) and proportional-integral (PI) controllers is used. The parameters of the controllers are tuned by computational optimization techniques for a doubly-fed induction generator (DFIG)-based WTS. The study is carried out on a 9 MW DFIG based WTS model in MATLAB/SIMULINK. Two computational optimization techniques: particle swarm optimization (PSO), as warm intelligence algorithm, and a genetic algorithm (GA), an evolutionary algorithm, are applied. A multi-objective, multi-dimensional error function is defined and minimized by selecting an appropriate error criterion for each objective of the function which depicts the relative magnitude of each objective in the error function. The results of the output power flow and the dynamic response of the optimized P and PI controllers are compared with the conventional P and PI controller in three different cases. It is revealed that the PSO-based controllers performed better in comparison with both the conventional controllers and the GA-based controllers.

Original languageEnglish
Article number1290
Number of pages18
Issue number8
Publication statusPublished - 18 Apr 2022


  • wind turbine system
  • doubly-fed induction generator
  • particle swarm optimization (PSO)
  • genetic algorithm (GA)
  • PI controller
  • computational intelligence

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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