Active disturbance rejection based MPPT control for wind energy conversion system under uncertain wind velocity changes

Lei, Zhendong; Sun, Xiaoming; Xing, Bowen; Hu, Yuan; Jin, Guangzhe

doi:10.1063/1.5037916

Cited by 5 publications

(9 citation statements)

References 35 publications

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“…is the gain of the observer z1 and z2 are respectively the estimation of y and f which represent the output of the ESO. Thus, the system of equations of the extended state observer is given as follow [4,20].…”

Section: Design Of Adrc Controllermentioning

confidence: 99%

See 2 more Smart Citations

Comparative Study of Active Disturbance Rejection Control with RST Control for Variable Wind Speed Turbine Based on Doubly Fed Induction Generator Connected to the Grid

Chakib¹,

Nasser²,

Essadki³

2020

IJIES

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In this paper, we propose a new control strategy called linear active disturbance rejection control (ADRC) used to control the wind energy conversion system (WECS) based on doubly-fed induction generator (DFIG). This recent control strategy is compared with the conventional RST polynomial control method considered better and more efficient than the classical PI method according to different works. By the extended state observer ESO of the ADRC controller, the internal and the external disturbances on the system are estimated and compensated as a total disturbance in real time. Moreover, the proposed ADRC method is easy to tune and more practical which has only one tuning parameter. The RST controller has three polynomials chosen in order to reduce the effect of disturbance. These controllers have been used to control the stator powers of DFIG in order to extracting the maximum energy produced by the wind by using a maximum power point tracking (MPPT), to regulate the dc-link voltage in order to maintain DC bus voltage at constant value and to regulate the reactive power to ensure a unitary power factor. Then, these both control strategies are designed and their performances are compared in order to deduce the most efficient in terms of reference tracking and robustness. The simulation results prove that the proposed ADRC control technique is more robust and have better performance than the RST control.

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Section: Design Of Adrc Controllermentioning

confidence: 99%

“…Where, KP is the control parameter of the linear ADRC and r is the reference input signal [4,20]. Generally:…”

Section: Design Of Adrc Controllermentioning

confidence: 99%

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Comparative Study of Active Disturbance Rejection Control with RST Control for Variable Wind Speed Turbine Based on Doubly Fed Induction Generator Connected to the Grid

Chakib¹,

Nasser²,

Essadki³

2020

IJIES

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“…2. Several MPPT control strategies have been proposed in the literature [13][14][15][16]. The MPPT employed in this study relies on the Tip Speed Ratio (TSR) control, which regulates the rotor speed, while keeping the TSR at its optimum value to capture the maximum wind power, at this value, C p λ β , ( ) is equal to its maximum value that is C p max achieved for β = 0 [13][14][15][16][17] according to Eq.…”

Section: Voltage Source Converter Modelmentioning

confidence: 99%

Optimal DTC Control Strategy of DFIG Using Variable Gain PI and Hysteresis Controllers Adjusted by PSO Algorithm

Amer

Miloudi

Lakdja

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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This paper presents an optimal Direct Torque Control (DTC) strategy for Doubly Fed Induction Generator based wind turbine. The proposed strategy is considered based on Particle Swarm Optimization (PSO) Algorithm. The PSO is found to be robust and fast in solving nonlinear problems. Motivation for application of PSO approach is to overcome the limitation of the conventional controllers design, which cannot guarantee satisfactory control performance when designed by trial and error. In this work PSO algorithm was used to adjust the hysteresis torque and flux comparators bandwidths and to tune the parameters of Variable Gain PI (VGPI) controller designed for Maximum Power Point Tracking (MPPT) speed control of wind turbine to ensure high performance torque control. The optimal control strategy is considered in detail and it is shown that the use of the optimized controllers reduces rotor flux and electromagnetic torque ripples and improves the system dynamic performances. The effectiveness of the proposed direct torque control based on PSO algorithm (optimal DTC) method is illustrated through simulations on 1.5 MW DFIG based wind turbine. Simulation results illustrate the improved performances of optimal DTC compared with the conventional DTC.

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“…A WPGS should be capable of extracting power from the wind in case of above or below rated wind speed conditions and it is possibly achieved by the means of the maximum power point technique (MPPT) controller (Huang et al, 2017). Numerous robust MPPT methodologies have been developed to extract optimal power from wind (Heier, 2014) and the popular methodologies include tip speed ratio (TSR) (Msirdi et al, 2015; Parker and Leftwich, 2016), power signal feedback (PSF) (Kumar and Chatterjee, 2016; Merabet et al, 2017), hill-climb searching (HCS) (Ardjal et al, 2018; Dinh and Ahn, 2017), and optimal torque control (OTC) (Boulouiha et al, 2015; Dahbi et al, 2016; Lei et al, 2018; Nasiri et al, 2014). The TSR methodology extracts optimal power through diminishing the generator speed by estimating the wind speed (Liu et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

An improved radial basis function neural network control strategy-based maximum power point tracking controller for wind power generation system

Sitharthan¹,

Parthasarathy²,

Rani

et al. 2019

Transactions of the Institute of Measurement and Control

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This literature presents an improved maximum power point tracking (MPPT) controller based on radial basis function neural network (RBFNN) control strategy to extract optimal power for wind power generation system. The proposed RBFNN controller is trained online using gradient descent algorithm and its network learning rate modification is carried out by the modified particle swarm optimization algorithm. The proposed MPPT controller uses optimal torque control methodology to extract optimal power available in the wind by upholding the generated torque at an optimal level. The most promising aspects of the proposed controller are that it not only extracts maximum available power from wind, but it also rapidly responses to the change in wind speeds and maintains converter with negligible converter losses. To evaluate the performance of the proposed MPSO-RBFNN-based MPPT controller, an extensive simulation study and experimental analysis is performed. The attained results confirm the enhanced performance of the proposed MPPT controller.

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Active disturbance rejection based MPPT control for wind energy conversion system under uncertain wind velocity changes

Cited by 5 publications

References 35 publications

Comparative Study of Active Disturbance Rejection Control with RST Control for Variable Wind Speed Turbine Based on Doubly Fed Induction Generator Connected to the Grid

Comparative Study of Active Disturbance Rejection Control with RST Control for Variable Wind Speed Turbine Based on Doubly Fed Induction Generator Connected to the Grid

Optimal DTC Control Strategy of DFIG Using Variable Gain PI and Hysteresis Controllers Adjusted by PSO Algorithm

An improved radial basis function neural network control strategy-based maximum power point tracking controller for wind power generation system

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