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Tuning of DFIG Wind Turbine Controllers with Voltage Regulation Subjected to Electrical Faults Using a PSO Algorithm

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Abstract

The doubly fed induction generator (DFIG) wind turbine is the most used in wind generation, and there are different control strategies for this type of machine. The correct choice of the proportional-integral (PI) controller parameters values determine the stability and performance of the DFIG when subjected to a transient disturbances. This research considers the DFIG with active power and voltage (PV) control loops, and seeks to adjust the PI controllers parameters to obtain a damped behavior and small peaks in the electrical and mechanical variables when the wind turbine is subjected to electrical faults. For the tuning, a particle swarm optimization (PSO) algorithm that minimizes an objective function (OF) is proposed, derived from the weighting of three objectives related to the dynamic performance of the wind turbine during the fault. In addition, for comparative purposes another tuning is performed via the “trial and error” method (T&E). The results of computer simulations showed that the PSO is an effective tool for this nonlinear and continuous problem, achieving an adequate tuning of the PI controller parameters, in addition to showing the difficulties of the “trial and error” method, as it is not systematic. The proposed PSO method provided a tuning improving the performance of the penalized quantities, damping the electrical and mechanical oscillations, with low peaks in the active power, terminal voltage remained within the pre-established limits, and preserving performance for different fault intensities and shaft stiffness variations.

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Abbreviations

PV:

Active power and voltage

DC:

Direct current

DFIG:

Doubly fed induction generator

GC:

Grid code

Ti:

Integral time (parameter)

IAE:

Integral absolute error

LVRT:

Low voltage ride through

MPPT:

Maximum power point tracking

OF:

Objective function

PSO:

Particle swarm optimization

\(C_p\) :

Performance coefficient

K:

Proportional (parameter)

PI:

Proportional-integral

RSC:

Rotor side converter

\(K_s\) :

Torsional stiffness coefficient

T&E:

Trial and error

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Acknowledgements

The authors would like to thank São Carlos Engineering School, University of São Paulo (USP), as well as, Western Parana State University (UNIOESTE) for supporting this research.

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Authors and Affiliations

  1. Sao Carlos School of Engineering, University of Sao Paulo-USP, Av. Trab. São Carlense, 400, Sao Carlos, SP, Brazil

    Milton Ernesto Barrios Aguilar & Denis Vinicius Coury

  2. Western Parana State University - UNIOESTE, Av. Tarquánio Joslin dos Santos, 1300, Foz do Iguacu, PR, Brazil

    Fernanda Ribeiro Machado & Romeu Reginatto

Authors
  1. Milton Ernesto Barrios Aguilar
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  2. Denis Vinicius Coury
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  3. Fernanda Ribeiro Machado
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  4. Romeu Reginatto
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Correspondence to Milton Ernesto Barrios Aguilar.

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Ethical Approval

This work is an extended version with new analyses and results of article Aguilar et al. (2020a), presented at “VIII Simpósio Brasileiro de Sistemas Elétricos” (SBSE 2020).

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The authors would like to thank São Carlos Engineering School, University of São Paulo (USP), Western Parana State University (UNIOESTE) for the financial support.

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Aguilar, M.E.B., Coury, D.V., Machado, F.R. et al. Tuning of DFIG Wind Turbine Controllers with Voltage Regulation Subjected to Electrical Faults Using a PSO Algorithm. J Control Autom Electr Syst 32, 1417–1428 (2021). https://doi.org/10.1007/s40313-021-00779-w

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  • DOI: https://doi.org/10.1007/s40313-021-00779-w

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