Vector control strategy for a doubly-fed stand-alone induction generator

Forchetti, Daniel Gustavo; García, Guillermo; Valla, M.I.

doi:10.1109/iecon.2002.1185407

Cited by 54 publications

(40 citation statements)

References 8 publications

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“…Les équations de la MADA dans un repère quelconque sont les suivantes [11] : (3,4,6), σ étant le coefficient de dispersion de la MADA, la contrainte (9) correspond à la bonne orientation du repère choisi [3,4,11] :…”

Section: Modele Et Principe De Commande De La Machine Synchrone Aunclassified

Commande d'un système de génération électrique pour réseau de bord d'avion. Introduction de charges non linéaires et mise en place d'un filtre LC

Khatounian¹,

Khatounian²,

Berthereau³

et al. 2005

J3eA

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Section: Modele Et Principe De Commande De La Machine Synchrone Aunclassified

Commande d'un système de génération électrique pour réseau de bord d'avion. Introduction de charges non linéaires et mise en place d'un filtre LC

Khatounian¹,

Khatounian²,

Berthereau³

et al. 2005

J3eA

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“…Several fieldoriented control schemes for the DFIG have been proposed for the applications of both types [18][19][20][21][22][23], and the control strategies of the grid side and rotor side converters for the grid-connected type and stand-alone type are quite different. For the grid-connected type DFIG system proposed in [18], the design of the field-oriented control for the grid side converter is to provide independent control of the output real and reactive power with the regulating of DC-link voltage.…”

Section: Introductionmentioning

confidence: 99%

“…For the stand-alone type DFIG system proposed in [20], an indirect stator-oriented vector control for the rotor side converter was designed to provide stable stator voltage through the control of the stator magnetizing current with the regulating of DC-link voltage in the grid side converter. Furthermore, various control schemes were designed for the rotor side converter using the fieldoriented control scheme to control the magnitude and frequency of the stator voltage with the DC-link voltage regulation via the grid side converter [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Intelligent-controlled doubly fed induction generator system using PFNN

Lin

Huang

Tan

et al. 2012

Neural Comput & Applic

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An intelligent-controlled doubly fed induction generator (DFIG) system using probabilistic fuzzy neural network (PFNN) is proposed in this study. This system can be applied as a stand-alone power supply system or as the emergency power system when the electricity grid fails for all sub-synchronous, synchronous, and super-synchronous conditions. The rotor side converter is controlled using the field-oriented control to produce three-phase stator voltages with constant magnitude and frequency at different rotor speeds. Moreover, the grid side converter, which is also controlled using field-oriented control, is primarily implemented to maintain the magnitude of the DC-link voltage. Furthermore, an intelligent PFNN controller is proposed for both the rotor and grid side converters to improve the transient and steady-state responses of the DFIG system at different operating conditions. The network structure, online learning algorithm, and convergence analyses of the PFNN are introduced in detail. Finally, the feasibility of the proposed control scheme is verified using some experimental results.

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“…In this regard, the vector control strategy described in [15] - [18] can be used as a basis for implementing the DFIG and its associated control. The Rotor Side Converter (RSC) has been used to control the system voltage and frequency whereas the Line Side Converter (LSC) has been used to regulate the DC link voltage regardless of the power flow direction of the backback converter system.…”

Section: A Wind Turbine Generatormentioning

confidence: 99%