State estimation of DFIG using an Extended Kalman Filter with an augmented state model

Malakar, Mridul Kanti; Tripathy, Praveen; Krishnaswamy, Srinivasan

doi:10.1109/npsc.2014.7103891

Cited by 12 publications

(15 citation statements)

References 11 publications

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“…6" shows the block diagram of voltage control of the DC-Link voltage by GSC. This diagram consists of an internal loop for controlling converter current and an external loop for controlling and regulating the DC-Link voltage [21]- [22]. In order to prevent dynamic interference between internal and external loops, the bandwidth of the internal loop is considered much larger than that of the external loop.…”

Section: Designing Of Esomentioning

confidence: 99%

“…In this paper, for controlling the DC-Link voltage, an Expanded State Observer (ESO) based on a Generalized Proportional-Integral (GPI) controller is introduced. In this controller, due to using the GPI controller, the improved dynamic response is resistant against voltage changes, and settling time is reduced [19]- [22]. In recent years, there have been numerous researches about enhancing Low Voltage Ride-Through (LVRT) capability of DFIG.…”

Section: Introductionmentioning

confidence: 99%

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Improved Low Voltage Ride-Through Capability of DFIG with ESO Controller under Unbalanced Network Conditions

Vali

Hosseni

Olamaei

2021

mjee

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Under unbalanced grid condition, in a Doubly-Fed Induction Generator (DFIG), voltage, current, and flux of the stator become asymmetric. Therefore, active-reactive power and torque will be oscillating. In DFIG controlling Rotor Side Converter (RSC) aims to eliminate power and torque oscillations. However, simultaneous elimination of the power and torque oscillations is not possible. Also, Grid Side Converter (GSC) aims to regulate DC-Link voltage. In this paper, in order to regulate DC-Link voltage, an Extended State Observer (ESO) based on a Generalized Proportional-Integral (GPI) controller, is employed. In this controlling method, DC-Link voltage is controlled without measuring the GSC current, and due to using the GPI controller, the improved dynamic response is resistant against voltage changes, and the settling time is reduced. To improve the transient stability and Low Voltage Fault Ride Through (LVRT) capability of DFIG, Statistic Fault Current Limiter (S-FCL) and Magnetic Energy Storage Fault Current Limiter (MES-FCL) are proposed in this paper. The proposed FCL does not only limit the fault current but also fasten voltage recovery. The simulations are implemented by MATLAB software in the synchronous positive and negative sequence reference (d-q).

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Section: Designing Of Esomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Low Voltage Ride-Through Capability of DFIG with ESO Controller under Unbalanced Network Conditions

Vali

Hosseni

Olamaei

2021

mjee

View full text Add to dashboard Cite

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“…Although accurate modelling and estimation of DFIGs improve monitoring and control of DFIG, it has not been studied sufficiently. Pérez et al (2012), Malakar et al (2014), Shahriari et al (2016b) and Shahriari et al (2018) are some of the studies on this subject. Pérez et al (2012) and Malakar et al (2014) consider a sixth-order model for DFIG and neglect most of the state variables, especially those related to the controllers and grid-side filter current.…”

Section: Introductionmentioning

confidence: 99%

“…Pérez et al (2012), Malakar et al (2014), Shahriari et al (2016b) and Shahriari et al (2018) are some of the studies on this subject. Pérez et al (2012) and Malakar et al (2014) consider a sixth-order model for DFIG and neglect most of the state variables, especially those related to the controllers and grid-side filter current. This deficiency is shown by comparing the estimation results of our DFIG model with results of Malakar et al (2014).…”

Section: Introductionmentioning

confidence: 99%

Modelling and dynamic state estimation of a doubly fed induction generator wind turbine

Shahriari

2020

COMPEL

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Purpose This paper aims to propose an 18th-order nonlinear model for doubly fed induction generator (DFIG) wind turbines. Based on the proposed model, which is more complete than the models previously developed, an extended Kalman filter (EKF) is used to estimate the DFIG state variables. Design/methodology/approach State estimation is a popular approach in power system control and monitoring because of minimizing measurement noise level and obtaining non-measured state variables. To estimate all state variables of DFIG wind turbine, it is necessary to develop a model that considers all state variables. So, an 18th-order nonlinear model is proposed for DFIG wind turbines. EKF is used to estimate the DFIG state variables based on the proposed model. Findings An 18th-order nonlinear model is proposed for DFIG wind turbines. Furthermore, based on the proposed model, its state variables are estimated. Simulation studies are done in four cases to verify the ability of the proposed model in the estimation of state variables under noisy, wind speed variation and fault condition. The results demonstrate priority of the proposed model in the estimation of DFIG state variables. Originality/value Evaluating DFIG model to estimate its state variables precisely.

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“…In [31], an EKF was proposed as the rotor position estimator, and the observability of the DFIG was analysed. In [32], a comprehensive analysis of the performance of an EKF was carried out for the non-augmented, partially-augmented and augmented state models of DFIG, respectively, and the best performance was obtained when applying the proposed augmented state estimator. Furthermore, a sensorless optimal power control of brushless DFIG (BDFIG) based on EKF was investigated in [33].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control of Late-Stage Offshore DFIG-WT with FSTP Converters by Using EKF to Ride through Hybrid Faults

et al. 2017

Energies

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Abstract:A hybrid fault scenario in a late-stage offshore doubly-fed induction generator (DFIG)-based wind turbine (DFIG-WT) with converter open-circuit fault and position sensor failure is investigated in this paper. An extended Kalman filter (EKF)-based sensorless control strategy is utilized to eliminate the encoder. Based on the detailed analysis of the seventh-order dynamic state space model of DFIG, along with the input voltage signals and measured current signals, the EKF algorithm for DFIG is designed to estimate the rotor speed and position. In addition, the bridge arm open circuit in the back-to-back (BTB) power converter of DFIG is taken as a commonly-encountered fault due to the fragility of semiconductor switches. Four-switch three-phase (FSTP) topology-based fault-tolerant converters are employed for post-fault operation by considering the minimization of switching losses and reducing the circuit complexity. Moreover, a simplified space vector pulse width modulation (SVPWM) technique is proposed to reduce the computational burden, and a voltage balancing scheme is put forward to increase the DC-bus voltage utilization rate. Simulation studies are carried out in MATLAB/Simulink2017a (MathWorks, Natick, MA, USA) to demonstrate the validity of the proposed hybrid fault-tolerant strategy for DFIG-WT, with the wind speed fluctuation, measurement noises and grid voltage sag taken into consideration.

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State estimation of DFIG using an Extended Kalman Filter with an augmented state model

Cited by 12 publications

References 11 publications

Improved Low Voltage Ride-Through Capability of DFIG with ESO Controller under Unbalanced Network Conditions

Improved Low Voltage Ride-Through Capability of DFIG with ESO Controller under Unbalanced Network Conditions

Modelling and dynamic state estimation of a doubly fed induction generator wind turbine

Sensorless Control of Late-Stage Offshore DFIG-WT with FSTP Converters by Using EKF to Ride through Hybrid Faults

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