Improved wind system using non-linear power control

Ihedrane, Yasmine; Bekkali, Chakib El; Ghamrasni, Madiha El; Mensou, Sara; Bossoufi, Badre

doi:10.11591/ijeecs.v14.i3.pp1148-1158

Cited by 23 publications

(20 citation statements)

References 13 publications

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“…The objective of this control is to keep the amplitude of the voltage equal to that of the grid by acting on the voltage of the DC bus. For that, we define the error of continuation of this state variable, such as [24]

e_{V_{dc}} = V_{dc_ref} - V_{dc}

From (33), we define the Lyapunov function such that

V_{1} = \frac{1}{2} e_{V_{normaldc}}^{2}

To ensure the stability of the system, we define a positive constant ‘kp’ in the derivative of (28), such that

{\dot{V}}_{1} = - K_{V_{dc}} e_{V_{dc}}^{2} + e_{V_{dc}} ()(, K_{V_{dc}} e_{V_{dc}} + {\dot{V}}_{Dc - ref} - \frac{P_{g} - P_{r}}{C \cdot V_{dc}})

According to the previous equation and with respect of the stability condition of the Lyapunov function, we will have [17]

({, \begin{matrix} P_{g_ref} = P_{g} \\ v_{s_ref} = \frac{P_{g_ref}}{C \cdot k_{v_{dc}} \cdot e_{v_{dc}}} - P_{normalr} \end{matrix})

…”

Section: Backstepping Control Techniquementioning

confidence: 99%

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DSPACE‐based implementation for observer backstepping power control of DFIG wind turbine

Bossoufi

Karim

Taoussi

et al. 2020

IET Electric Power Applications

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This work develops a real‐time implementation on the DSPACE environment of an adaptive non‐linear control strategy for a wind energy conversion system (WECS) based on the doubly‐fed induction generator (DFIG). The DSPACE‐DS1104 board is directly associated with an experimental bench of a wind power system. The non‐linear backstepping controller has been realised to control the active and reactive powers of the DFIG connected directly to the electricity grid via two converters (grid side and machine side). First, a full review of the WECS is discussed. Subsequently, a detailed description of the backstepping control laws based on the Lyapunov stability technique is reported. Consequently, a simulation on the Matlab & Simulink environment was carried out to test the proposed control model in terms of performance and robustness. The second part of this work was devoted to the experimental validation of the adaptive backstepping control algorithm on a test bench to prove its efficiency. The results obtained show a perfect correlation between simulations and experiments (in static and dynamic regime) even for fluctuating wind speed.

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e_{V_{dc}} = V_{dc_ref} - V_{dc}

From (33), we define the Lyapunov function such that

V_{1} = \frac{1}{2} e_{V_{normaldc}}^{2}

To ensure the stability of the system, we define a positive constant ‘kp’ in the derivative of (28), such that

{\dot{V}}_{1} = - K_{V_{dc}} e_{V_{dc}}^{2} + e_{V_{dc}} ()(, K_{V_{dc}} e_{V_{dc}} + {\dot{V}}_{Dc - ref} - \frac{P_{g} - P_{r}}{C \cdot V_{dc}})

According to the previous equation and with respect of the stability condition of the Lyapunov function, we will have [17]

({, \begin{matrix} P_{g_ref} = P_{g} \\ v_{s_ref} = \frac{P_{g_ref}}{C \cdot k_{v_{dc}} \cdot e_{v_{dc}}} - P_{normalr} \end{matrix})

…”

Section: Backstepping Control Techniquementioning

confidence: 99%

“…DC-bus controller:The objective of this control is to keep the amplitude of the voltage equal to that of the grid by acting on the voltage of the DC bus. For that, we define the error of continuation of this state variable, such as[24] …”

mentioning

confidence: 99%

DSPACE‐based implementation for observer backstepping power control of DFIG wind turbine

Bossoufi

Karim

Taoussi

et al. 2020

IET Electric Power Applications

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“…Maximization of power control without speed control. while the variation of the wind speed in steady state is low compared to the electrical time constants of the system, we assume that the speed of rotation of the DFIG is fixed and neglecting the effect of the viscous torque f, the dynamic equation of the turbine becomes (12); from (12) we obtain the static equation describing the stationary state of the turbine (13); The reference electromagnetic torque is determined from an estimate of the aerodynamic torque given by (14),we obtain equation (15); The orientation angle of the blades β is assumed to be constant and the estimated speed of the turbine is calculated from the mechanical speed ( 16); The estimated wind speed is given by equation ( 17);on the Base of the previous equations, we can then write the equation of the reference electromagnetic couple (18). .…”

Section: Wind-turbine Modelmentioning

confidence: 99%

Improvement of Sliding Mode Power Control for WECS based on DFIG-Generator

Majout

Abrahmi

Ihedrane

et al. 2020

Wseas Transactions on Computer Research

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In this work, we are developing a new strategy for controlling wind systems based on the DFIG Generator. The SMC sliding mode technique is based on the principle of Lyapunov stability in order to make a nonlinear system close to linearity. The use of such a technique with an improvement in regulators to eliminate the Chattering phenomenon shows a great improvement in the performance of wind systems. which is based on performance estimators to improve the quality of the system. The energy quality at the output of the wind system will be injected into the distribution network according to international standards. The proposed model is validated on the Matlab & Simulink environment to test trajectory tracking and robustness.

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“…The study [15] introduced a sliding mode controller to solve the above constraints. In recent years, the sliding mode controller, which is powerful in controlling both linear and nonlinear objects, has been examined by various researchers.…”

Section: Introductionmentioning

confidence: 99%

Fractional-order sliding mode controller for the two-link robot arm

Nguyen¹

2020

IJECE

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In this paper, the author proposes a sliding mode controller with the fractional-order for the two-link robot arm. Firstly, the model and dynamic equations of the two-link robot arm are presented. Based on these equations, the author builds the controller for each joint of the robot. The controller is a sliding mode controller with its order is not an integer value. The task of the controller is to adjust the torques acted on the joints in order for the angular coordinates of each link to coincide with the desired values. The effectiveness of the proposed control system is demonstrated through Matlab-Simulink software. The robot model and controller are built to investigate the system quality. The results show that the quality of the control system is very high: there is not the chattering phenomenon of torques, the response angles of each link quickly reach the desired values, and the static error equal to zero.

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Improved wind system using non-linear power control

Cited by 23 publications

References 13 publications

DSPACE‐based implementation for observer backstepping power control of DFIG wind turbine

DSPACE‐based implementation for observer backstepping power control of DFIG wind turbine

Improvement of Sliding Mode Power Control for WECS based on DFIG-Generator

Fractional-order sliding mode controller for the two-link robot arm

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