Dynamic DFIG wind farm model with an aggregation technique

Chowdhury, M. A.; Hosseinzadeh, Nasser; Billah, Md. Maruf; Haque, S. A.

doi:10.1109/icelce.2010.5700695

Cited by 21 publications

(13 citation statements)

References 9 publications

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“…For the current operating conditions discussed earlier the (C3) modes (11,20) are dominated by (C2) modes (10,9) which have almost the same frequency but with less damping as shown in Fig. 7a.…”

Section: Case Imentioning

confidence: 68%

“…Detailed WF models are used for the detailed, internal engineering work for the WF design and layout. Using this detailed modelling method for studying a large number of WTs will result in a higher order and complex model which will considerably increase the computational time [10,11]. In this model, every turbine is modelled with its full power and control systems.…”

Section: Detailed Modelmentioning

confidence: 99%

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Wind farm dynamic models assessment under weak grid conditions

Morgan

Eldeib

El-Marsafawy

2018

IET Renewable Power Generation

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Large-scale integration of wind power is one of the main challenges in today's power systems. Therefore, there is an increased importance to generate more accurate yet simplified wind farm (WF) models. The current modelling techniques of WFs depend on aggregationto reduce the degree of model complexity and computational time. The two techniques of aggregation are adopted in the literature: fully aggregated model (FAM) and multi-machine model where the WF is divided into a number of aggregated models for different sections of the WF. A small-signal model based comparison between the two techniques of aggregation is introduced in this study. The aim is to investigate the impacts of the full aggregation of the wind turbines on the overall system critical modes under weak grid conditions as compared to the multi-machine modelling approach. The comparison is done for different operating conditions (output active and reactive power) of the WF and also under different short-circuit ratios to reveal to what extent the FAM can be relied on to provide an accurate response of large WFs.

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Section: Case Imentioning

confidence: 68%

Section: Detailed Modelmentioning

confidence: 99%

Wind farm dynamic models assessment under weak grid conditions

Morgan

Eldeib

El-Marsafawy

2018

IET Renewable Power Generation

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“…where C is the dc-link capacitance, v dc is the voltage of the dc-link capacitor and R loss is the total conducting and switching losses of the converter, P r (t) is the instantaneous input rotor power and P g (t) is the instantaneous output power of the GSC. P r and P g are given by Chowdhury et al [22]…”

Section: Research Articlementioning

confidence: 99%

“…The dc‐link voltage dynamics can be written as

C v_{dc} {\dot{v}}_{dc} = - \frac{v_{dc}^{2}}{R_{loss}} - P_{r} (t) - P_{g} (t)

where C is the dc‐link capacitance, v dc is the voltage of the dc‐link capacitor and R loss is the total conducting and switching losses of the converter, P r ( t ) is the instantaneous input rotor power and P g ( t ) is the instantaneous output power of the GSC. P r and P g are given by Chowdhury et al [22]

P_{normalr} = v_{rd} i_{rd} + v_{rq} i_{rq}

P_{normalg} = v_{gd} i_{gd} + v_{gq} i_{gq}

This paper proposes a control strategy based on the above‐described DFIG model for a single machine infinite bus test system in the following section.…”

Section: Dfig Modelmentioning

confidence: 99%

Robust active disturbance rejection controller design to improve low‐voltage ride‐through capability of doubly fed induction generator wind farms

Chowdhury

Sayem

Shen

et al. 2015

IET Renewable Power Generation

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This study presents the design of a robust active disturbance rejection (ADR) controller in order to improve lowvoltage ride-through (LVRT) capability of wind farms connected with doubly fed induction generator (DFIG). The ADR controller is particularly effective in real-time estimation and mitigation of the total effect of various uncertainties against a wide range of parameter variations, model uncertainties and large disturbances. The performance evaluation of the designed controller is performed on an IEEE system under different test cases. The simulation results show that the proposed controller is robust against uncertainties in operating conditions and successfully improves the damping and voltage stability and thus the LVRT capability of DFIGs.

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“…According to the obtained results for traditional DFIG vector controllers [26][27][28], the generator still operates within a specific range during a grid fault. Nevertheless, the proper dynamic response of two state variables, such as rotor voltage and rotor current, cannot be assured.…”

Section: Introductionmentioning

confidence: 95%

Improved Control of Grid-connected DFIG-based Wind Turbine using Proportional-Resonant Regulators during Unbalanced Grid

Karkri

Rey-Boué

Moussaoui³

et al. 2019

Energies

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The quality of power and current control are the greatest challenges of grid-connected wind farms during abnormal conditions. The negative-and positive-sequence components of the grid currents may be injected into a wind generation system during grid faults, which can affect the power stability and damage the wind system. The proposed work assures a low-voltage ride through capability of doubly-fed induction generator-based wind turbines under the grid voltage sag. A new technique to protect the wind system and to recompense the reactive power during failures of the utility grid according to the Spanish grid code is proposed. The control design is implemented to the power converters, and the grid current regulation is developed by using proportional-resonant regulators in a stationary two-phase (αβ) reference frame. The control performance is significantly validated by applying the real-time simulation for the rotor-side converter and the hardware in the loop simulation technique for the experiment of the generator's grid-side converter control.

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Dynamic DFIG wind farm model with an aggregation technique

Cited by 21 publications

References 9 publications

Wind farm dynamic models assessment under weak grid conditions

Wind farm dynamic models assessment under weak grid conditions

Robust active disturbance rejection controller design to improve low‐voltage ride‐through capability of doubly fed induction generator wind farms

Improved Control of Grid-connected DFIG-based Wind Turbine using Proportional-Resonant Regulators during Unbalanced Grid

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