Study of optimal control applied to a Doubly Fed Induction Generator attached to wind turbine system

Zgarni, Ines; Amraoui, Lilia El

doi:10.1109/energycon48941.2020.9236624

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…Thus, the effectiveness and the robustness of the studied controllers have also been tested at different disturbances in the mechanical torque of the wind turbine. In order to do this, Equations ( 7), (21), and ( 26) are modified as follows:…”

Section: Comparative Resultsmentioning

confidence: 99%

Disturbance rejection of the powers and DC ‐link voltage of a doubly‐fed induction generator using state‐space based linear quadratic integral optimal control approach

Bhushan

Kumar²,

Chatterjee

2021

Int Trans Electr Energ Syst

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In this paper, an optimal linear quadratic regulator (LQR)-based integral controller (i.e., linear quadratic integral [LQI]) has been designed with an innovative approach for the tracking problems of a wind-driven doubly-fed induction generator (DFIG) system. The main objective of this controller is to reject the deviations that occurred in the DFIG powers together with the DC-link voltage due to the perturbations in the stator voltage. The purpose of the inclusion of integral action with the well-known modern optimal controller LQR is to guarantee zero steady-state error for disturbance rejection/set-point tracking. Further, the genetic algorithm (GA) technique is included for the optimal design of the LQI weighting matrices, which rapidly, as well as effectively rejects the disturbances from the system by regulating the augmented state variables. Therefore, to overcome these issues we have chosen the appropriate control model, which controls as a whole, that is, a multi-input-multi-output (MIMO) system. The DFIG system is a MIMO system, which has been modeled in a state-space approach in the d-q axes rotating frame of reference. To examine the effectiveness and robustness of the suggested control strategy, small-signal stability has been done by eigen values and participation factors method on digital simulations in the MATLAB/Simulink environment. Furthermore, the optimal control solutions have been tested under the various larger List of Symbols and Abbreviations: Δ, small deviation; ϕ s , angle between the voltage of slack bus and DFIG bus; ψ qr , ψ dr , d-q axes components of the rotor flux linkages; ψ qs , ψ ds , d-q axes components of the stator flux linkages; ω B , base speed; ω r , generator-angular speed; ω s , synchronous angular speed; C dc , capacitance of the DC-link; f, nominal frequency; H, combined inertia of wind turbine and generator; i dc , DC-link capacitor current; i qg , i dg , d-q axes components of the GSC current; i qr , i dr , d-q axes components of the RSC current; i qs , i ds , d-q axes components of the stator side current; i qt , i dt , d-q axes components of the total transmission line current; I t , total transmission line current; L m

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Section: Comparative Resultsmentioning

confidence: 99%