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Communication Dans Un Congrès Année : 2017

Model Predictive Direct Power Control of Doubly Fed Induction Generator with Dead-Time Compensation

Résumé

The paper presents the control of a doubly fed induction generator connected with a three-level neutral point clamped inverter with compensation of dead-time effects. Model Predictive Direct Power Control is synthesized using a dynamical model of the doubly fed induction generator and three-level neutral point clamped inverter. The principle of the proposed control scheme is to use the dynamical model to compute predictions of the future values of the stator flux, rotor current and DC-link capacitor voltages for all possible configurations of voltage vectors. However, the dead-time to avoid the short circuit in the inverter also causes the modeling errors. Thus, by taking into account the dead-time in the model, it is possible compensate the dead-time effect of the switching devices. The active and reactive powers can be estimated based on the stator flux and the rotor current. The cost function considers the error between the active, reactive powers and their references, balance the DC-link capacitor voltage and reduce the switching frequency and common-mode voltage. The optimal switching state that minimizes the cost function is selected and applied to the inverter. The simulation results were carried out with Matlab under different conditions of wind speed and verifying the effectiveness of the proposed method. Keywords: Power Plants and Power Systems, Control of renewable energy resources, Application of power electronics, Intelligent control of power systems and Optimal operation and control of power systems.
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Dates et versions

hal-01813524 , version 1 (11-04-2020)

Identifiants

  • HAL Id : hal-01813524 , version 1

Citer

Binh Quang Van Ngo, Pedro Rodriguez-Ayerbe, Sorin Olaru, Silviu-Iulian Niculescu. Model Predictive Direct Power Control of Doubly Fed Induction Generator with Dead-Time Compensation. IFAC 2017 - 20th World Congress of the International Federation of Automatic Control, Jul 2017, Toulouse, France. ⟨hal-01813524⟩
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