Predictive encoderless control of back-to-back converter PMSG wind turbine systems with Extended Kalman Filter

Zhang, Zhenbin; Si, Guangye; Kennel, Ralph

doi:10.1109/spec.2016.7846202

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…The presented method improves the estimation of generator speed reference and can extract the optimum generator power, especially during the small oscillations of the wind speed. None of the papers that have tried to improve the estimation accuracy [22][23][24] and other papers presented so far have addressed this idea on the PMSG wind turbine by estimating unpredictable parameters, which can significantly improve the accuracy of MPPT implementation. For this purpose, the unpredictable parameters were first identified, and then the generator speed was determined by the uncertainty estimation of these parameters.…”

Section: Discussionmentioning

confidence: 99%

“…The results of this study are compared with the unscented Kalman filter (UKF) and EKF. Zhang [24] has introduced a novel control method for power system converters in a grid-connected PMSG-based wind turbine structure by employing predictive controllers and state estimators. The introduced method has acceptable performances at different wind speeds and load situations.…”

Section: Introductionmentioning

confidence: 99%

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MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System

et al. 2021

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Variable speed wind turbines are commonly used as wind power generation systems because of their lower maintenance cost and flexible speed control. The optimum output power for a wind turbine can be extracted using maximum power point tracking (MPPT) strategies. However, unpredictable parameters, such as wind speed and air density could affect the accuracy of the MPPT methods, especially during the wind speed small oscillations. In this paper, in a permanent magnet synchronous generator (PMSG), the MPPT is implemented by determining the uncertainty of the unpredictable parameters using the extended Kalman filter (EKF). Also, the generator speed is controlled by employing a fuzzy logic control (FLC) system. This study aims at minimizing the effects of unpredictable parameters on the MPPT of the PMSG system. The simulation results represent an improvement in MPPT accuracy and output power efficiency.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System

et al. 2021

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“…The results showed a good dynamic and steady-state performance. A new control for a grid-connected PMSG-based wind turbine structure was introduced in [15] by using the predictive controllers and state estimators. However, this method needs more parameter tuning efforts.…”

Section: Wecs System Modelingmentioning

confidence: 99%

Dynamic Performance Enhancement of a Direct-Driven PMSG-Based Wind Turbine Using a 12-Sectors DTC

Awwad

2022

WEVJ

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This paper focuses on the performance analysis, modeling, and control of permanent magnet synchronous generator (PMSG)-based wind energy conversion. This work analyzes controllers for the machine-side converter (MSC) and grid-side converter (GSC) and presents a new direct torque control (DTC) scheme based on a 12-sectors polygonal DTC for variable speed control of the PMSG. The proposed method solves the drawbacks faced by conventional six-sectors DTC control. The proposed method utilizes 12 sectors of 30° each compared to 60° in the conventional 6-sectors DTC. The 12-sectors technique was applied to voltages and flux vectors to increase the degrees of freedom for the selection of optimal vectors and, thus, reduce the torque ripple. This work analyzed the aforementioned DTC methods using MATLAB/Simulink, comparing the dynamic response of the proposed 12-sectors DTC with the conventional 6-sectors DTC control, and the results verified the effectiveness of the proposed DTC control.

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“…Control systems without encoder are also considered in [19], where EKF is used to estimate the state variables of a backto-back converter. Measurements obtained from PMUs are introduced in the EKF algorithm in [20].…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of Wind Turbines With PMSM Using Cubature Kalman Filters

Cagigal

Macías

Gómez-Expósito

2020

IEEE Trans. Power Syst.

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This paper presents a parameter estimation technique for a variable-speed wind turbine with permanent magnet synchronous generator and back-to-back voltage source converter. The proposed technique applies the cubature Kalman filter for the joint estimation of the system dynamic state and a modified set of parameters from which the original model parameters can be algebraically recovered. To the authors knowledge, this work is the first attempt to apply such an innovative technique to a PMSM detailed estimation model including the control parameters of the voltage source converter.

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Predictive encoderless control of back-to-back converter PMSG wind turbine systems with Extended Kalman Filter

Cited by 9 publications

References 11 publications

MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System

MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System

Dynamic Performance Enhancement of a Direct-Driven PMSG-Based Wind Turbine Using a 12-Sectors DTC

Parameter Estimation of Wind Turbines With PMSM Using Cubature Kalman Filters

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