Adaptation mechanism techniques for improving a model reference adaptive speed observer in wind energy conversion systems

Benzaouia, Soufyane; Rabhi, Abdelhamid; Zouggar, Smail

doi:10.1007/s00202-020-00984-x

Cited by 12 publications

(5 citation statements)

References 27 publications

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“…The adaptive back EMF observer establishes two independent modules through parameter identification theory, namely the reference and adjustable models. According to the mathematical model of the permanent magnet synchronous motor and the observer module, the reference model and the parameters to be identified are constructed to construct the adjustable model; the purpose is to identify the parameters of the motor [27], as shown in Figure 2 1 0…”

Section: Adaptive Parameter Identification Model Designmentioning

confidence: 99%

Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive Back-EMF Observer

Ye¹,

Cao²,

Duan³

et al. 2022

Preprint

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Aiming at the problem that the change of motor parameters in actual operation will significantly reduce the control accuracy of the motor, this paper proposes a sensorless control method of permanent magnet synchronous motor based on an adaptive back-EMF observer. In the sensorless vector control algorithm, the mathematical model of the permanent magnet synchronous motor based on the coordinate axis transformation is established, the flux linkage of the permanent magnet synchronous motor is identified online, and the motor model is updated with the specified parameters, to realize the analysis of the rotor position and the permanent magnet synchronous motor. Accurate control of rotational speed. The back-EMF observer and the adaptive back-EMF observer are verified in the simulation environment. The simulation results show that the adaptive back-EMF observer can quickly converge to the actual value and track the motor parameters well. Enabling highly accurate rotor speed and position estimation. Finally, the permanent magnet synchronous motor control platform is built in the laboratory. Under the condition of the parameter change of the permanent magnet synchronous motor, the online identification of the parameters and the accurate control of the speed of the permanent magnet synchronous motor can be realized.

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Section: Adaptive Parameter Identification Model Designmentioning

confidence: 99%

Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive Back-EMF Observer

Ye¹,

Cao²,

Duan³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The authors Benzaouia et al (2020), Jalal and Ganjefar (2019), Li et al (2019), Rezaei et al (2019) carried their work by modeling a conventional Permanent Magnetic Synchronous Generator (PMSG)-based wind turbine system to estimate and control the generator rotor speed and its output power while Srikanth and Thirumalaivasan (2022) presents a grid tied-DFIG model for the same purpose. Similarly, the author of Haile et al (2021), Tuka (2023), Tuka and Endale (2023)estimated the model of the same machine by taking the relationship between generator rotor speed with the speed of the wind under dynamic conditions.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the effect of parametric uncertainty on dynamic performances of doubly fed induction generator-based wind energy conversion system

Haile,

Tuka

2023

Wind Engineering

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The wind, stochastic in nature, is one of the fastest-growing and most promising renewable energy resources in the entire world. Thus, this paper investigates the influence of parameter uncertainties upon a dynamic performance of a grid-tied Doubly-Fed Induction Generator (DFIG)-based Wind Energy Conversion System (WECS). The main uncertain parameters found in the study are mutual and rotor winding reactances which occurred due to the variation of the angular positions of the rotor caused by varying wind speeds. The variation in the wind speed caused the generator rotor speed to deviate between 25% and 150%. Consequently, the rotor winding reactance of DFIG changes from its nominal value of 1.31 mΩ to between 0.983 and −0.655 mΩ; and the mutual reactance from its nominal value of 0.941 Ω to between 0.758 and −0.4708 Ω. As a result, the stator and rotor winding voltages and currents of the DFIG are uncertain.

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“…Proportional-integral-derivative (PID) controlled hydraulic pitch actuator, and Type-2 Fuzz logic-based pitch-angle control scheme (Naik et al, 2020) and fuzz logic-based PID controller is employed for the speed control of wind energy conversion system (Haile et al, 2021). The neuronal network, fuzzy logic, and neuro-fuzzy-based PI controllers are employed for pitch angle control of the wind turbine (Pandey et al, 2022; Soufyane et al, 2020). However, the overall performance of the wind energy conversion systems under varying wind speeds is not good.…”

Section: Introductionmentioning

confidence: 99%

“…To avoid such an effect, two independent controllers of the wind turbine in partial load and full load modes were used according to the status of wind speed (Sahoo et al, 2020). This causes the control system more complex and bulky size (Apata and Oyedokun, 2020; Habibi et al, 2022; Soufyane et al, 2020). To overcome the aforementioned constraints, this study proposed an optimal fractional order proportional-integral-derivative (FOPID) controller for the pitch angle of the wind turbine blade.…”

Section: Introductionmentioning

confidence: 99%

Optimal control of the electro-hydraulic actuator for variable pitch variable speed wind turbine: Performance enrichment

Alemu,

Ayenew

2023

Wind Engineering

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The wind energy generation system is complex because of varying wind speeds and its control systems to improve its ability of energy harvesting. This paper considers a hydraulic actuator-based variable-pitch angle control of a 1.5 MW wind turbine. The existing control systems of the pitch mechanism of the wind turbines are complex and bulky size. This study applied Genetic Algorithm based Proportional Integral Derivative Controller (GA-PID), Fractional Order Proportional Integral Derivative (FOPID), and Genetic Algorithm based Fractional Order Proportional Integral Derivative (GA-FOPID) controllers to adjust the pitch angle of the wind turbine blade. The performance of GA-FOPID, FOPID, and GA-PID controlled pitch angle is compared by considering different wind speeds. The GA-FOPID controller reduced the variation in mechanical power to 0.08% concerning the rated value and the variation in mechanical torque to 1.51% in comparison to the rated value. Therefore, the GA-FOPID controller shows better performance than the conventional PID.

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Adaptation mechanism techniques for improving a model reference adaptive speed observer in wind energy conversion systems

Cited by 12 publications

References 27 publications

Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive Back-EMF Observer

Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive Back-EMF Observer

Analysis of the effect of parametric uncertainty on dynamic performances of doubly fed induction generator-based wind energy conversion system

Optimal control of the electro-hydraulic actuator for variable pitch variable speed wind turbine: Performance enrichment

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