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Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques

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

Authors

Arsalan Khurshid

Muhammad Ali Mughal

Achraf Othman

Tawfik Al-Hadhrami

Harish Kumar

Imtinan Khurshid

Arshad



Abstract

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), a swarm 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.

Journal Article Type Article
Acceptance Date Apr 12, 2022
Online Publication Date Apr 18, 2022
Publication Date 2022
Deposit Date Apr 28, 2022
Publicly Available Date Apr 28, 2022
Journal Electronics
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 11
Issue 8
Article Number 1290
DOI https://doi.org/10.3390/electronics11081290
Keywords wind turbine system; doubly-fed induction generator; particle swarm optimization (PSO); genetic algorithm (GA); PI controller; computational intelligence
Public URL http://researchrepository.napier.ac.uk/Output/2866210

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