Validation of an integral sliding mode control for optimal control of a three blade variable speed variable pitch wind turbine

Saravanakumar, R.; Jena, Debashisha

doi:10.1016/j.ijepes.2015.01.031

Cited by 133 publications

(63 citation statements)

References 21 publications

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“…To capture maximum power from wind energy in Region II, the blade pitch angle should be fixed at β = 0. In this situation, the fifth order polynomial approximation can be developed for C p ( λ , β ), which provides the power coefficient as follows :

C_{p} ((),, λ, β) = a_{0} + a_{1} λ^{1} + a_{2} λ^{2} + a_{3} λ^{3} + a_{4} λ^{4} + a_{5} λ^{5}

…”

Section: Wind Turbine Modelmentioning

confidence: 99%

Fractional‐order back‐stepping sliding‐mode torque control for a wind energy conversion system

Talebi

Ganjefar

2018

Env Prog and Sustain Energy

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At below‐rated wind speeds, the main goal of a controller design is to maximize power coefficient and consequently captured power. Due to nonlinearities and uncertainties in wind turbine systems and rapid variations in the wind speed profiles, the need for more effective and robust controllers is inevitable. To optimize the captured power, the rotor angular speed must track the time variable reference value that requires fast reactions of the designed controller. In this article, an advanced controller called a back‐stepping sliding‐mode controller was proposed to improve the turbine efficiency at a below‐rated wind speed. The controller was designed based on the combination of the back‐stepping sliding mode approach and fractional order calculus. The stability of the proposed controller is analyzed using the Lyapunov stability criterion. Finally, numerical simulation results are presented and compared with integer order, back‐stepping sliding mode control to illustrate the effectiveness of the proposed method. The simulation results demonstrated that the proposed controller had a good transition response, a low tracking error, and a very fast reaction against rapid variations in the wind speed in comparison to the back‐stepping sliding mode controller. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13110, 2019

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C_{p} ((),, λ, β) = a_{0} + a_{1} λ^{1} + a_{2} λ^{2} + a_{3} λ^{3} + a_{4} λ^{4} + a_{5} λ^{5}

…”

Section: Wind Turbine Modelmentioning

confidence: 99%

Fractional‐order back‐stepping sliding‐mode torque control for a wind energy conversion system

Talebi

Ganjefar

2018

Env Prog and Sustain Energy

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“…ISMC systems have been successfully implemented for aerospace applications, control a nonlinear stochastic system, pneumatic force servo system, etc. Several studies have implemented ISMC approaches to WECS successfully . In order to reduce chattering effect continuous approximation with quasi‐SMC, second‐ or higher‐order SM (HOSM) method have been employed.…”

Section: Introductionmentioning

confidence: 99%

Disturbance observer‐based integral sliding mode control for wind energy conversion systems

et al. 2020

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Recently, wind power production has been under the focus in generating power and became one of the main sources of alternative energy. Generating of maximum power from wind energy conversion system (WECS) requires accurate estimation of aerodynamic torque and uncertainties presented in the system. The current paper proposed the generalized high‐order disturbance observer (GHODO) with integral sliding mode control (ISMC) for extraction of maximum power via variable speed wind turbine by accurate estimation of wind speed. The assumption in previous works that considers the aerodynamic torque as slow‐varying is not applicable for the real system. Therefore, the high‐order disturbance observers were designed for precise estimation of uncertainties with fast‐changing behavior. A robust control system was designed to control the speed of the rotor at the optimal speed ratio. The obtained simulation results have shown the better performance characteristics than conventional linear quadratic regulator (LQR) approach. The stability of the proposed algorithm was proven by Lyapunov stability anaysis. Simulations results were obtained in Matlab/Simulink environment.

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“…Among them, the polynomial WSE techniques are simple and have quick restraint with convenient accuracy. They utilize the approximation of power coefficient polynomial equations with different order equations to calculate the wind speed . Alternatively, the DPC tracks the MPP by monitoring the power variations associated with the wind velocity.…”

Section: Introductionmentioning

confidence: 99%

Study of robust adaptive step‐sizes P&O MPPT algorithm for high‐inertia WT with direct‐driven multiphase PMSG

Mousa

Youssef

Mohamed

2019

Int Trans Electr Energ Syst

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Summary In this study, an efficient robust adaptive perturb and observe (RA‐PO) maximum power point tracking (MPPT) algorithm–based wind energy conversion system (WECS) is suggested to avoid drawbacks of conventional P&O (CPO) algorithms. It depends on observing the distance between the actual and optimal rotor speed, calculating the required adaptive ratio at each operating point, perturbing the rotor speed with an appropriate step‐size, and observing power variations until the P‐ω curve slope equals zero. Therefore, it exhibits a rapid speed tracking with low oscillations. Moreover, it offers a well‐defined relationship among the extracted mechanical power, the rotor speed, the perturbing step‐size, and the operating wind speed so wrong direction and loss of tracking problems can be avoided on high‐inertia wind turbine (WT) during rapid wind speed fluctuations. It improves the WECS efficiency from 87% to 91%. The performance of WECS is confirmed via MATLAB/SIMULINK.

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Validation of an integral sliding mode control for optimal control of a three blade variable speed variable pitch wind turbine

Cited by 133 publications

References 21 publications

Fractional‐order back‐stepping sliding‐mode torque control for a wind energy conversion system

Fractional‐order back‐stepping sliding‐mode torque control for a wind energy conversion system

Disturbance observer‐based integral sliding mode control for wind energy conversion systems

Study of robust adaptive step‐sizes P&O MPPT algorithm for high‐inertia WT with direct‐driven multiphase PMSG

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