Hybrid control based on sliding mode fuzzy of DFIG power associated
          WECS

The current study presents a robust sensorless control using passivity based control (PBC) combined with high gain observer (HGO). The proposed controller is applied to control the generated doubly-fed induction generator (DFIG) active and reactive power installed on a variable speed wind energy conversion system. The control objective is used to regulate independently the DFIG stator active and reactive power, which are decoupled by using the field oriented control technique. Additionally, this process leads to reduce the cost of control scheme by eliminating the speed sensor. Firstly, the DFIG is modeled under the port controlled Hamiltonian (PCH) model, as well as the method of simultaneous injection damping. Then, the DFIG is further modeled by assignment passivity based on the simultaneous injection damping and assignment (SIDA-PBC) control of the obtained model under such conditions and a comparison with the fuzzy sliding mode controller is carried out. Furthermore, the HGO is selected in order to estimate the rotor position and the speed from the measurement of the DFIG currents and voltages, and compared with fuzzy sliding mode observer. For testing the proposed control scheme performance, a 1.5 MW DFIG system is developed and simulated using MATLAB/Simulink. The obtained results demonstrate the effectiveness of the proposed control scheme in the presence of various DFIG parameters variation. Additionally, the control objective is achieved without speed sensor.

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“…The DFIG model in d-q reference frame is expressed as follow (Boualouch et al, 2017; Saihi et al, 2019):…”

Section: Dfig Integrated To Wind Power Systemmentioning

confidence: 99%

“…To design the DFIG powers control, a relationship between the rotor currents and rotor voltage is needed, this relation is expressed as follows: (Saihi et al, 2019; Wang et al, 2014):…”

Section: Dfig Integrated To Wind Power Systemmentioning

confidence: 99%

Sensorless passivity based control of doubly-fed induction generators in variable-speed wind turbine systems based on high gain observer

et al. 2022

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“…As opposed to that, the chattering phenomenon is still the major challenge of SMC that have to solve, to reduce the impact of chattering, numerous techniques have been suggested [23]. Research by Boubzizi et al [24] sliding mode (SM) strategy is employed to regulate the stator power of DFIG connected directly to the grid compared with a PI and adaptive fuzzy logic (AFLC), the SM control gives the best results and presents high performances compared with PI and ALFC, despite that it doesn't limit the chattering effect which can make the system unstable [25].…”

Section: Introductionmentioning

confidence: 99%

Hybrid sliding neural network controller of a direct driven vertical axis wind turbine

Bakou

Abid²,

Saihi³

et al. 2023

Bulletin EEI

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This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) scheme for controlling the stator power (active/reactive) of a doubly fed induction generator (DFIG)-based direct drive vertical axis wind turbine (VAWT) power system under a real-world scenario wind speed that will be installed in the Adrar region (Saharan zone) of Algeria. The SM-ANN scheme will control the stator power of the direct drive VAWT power. The chattering phenomenon is the most significant disadvantage associated with sliding mode control (SMC). In order to find a solution to this issue, the artificial neural network (ANN) method was applied to pick the appealing part of the SMC. MATLAB/Simulink is used to do an evaluation, after which the SM-ANN controller being suggested is compared to both traditional sliding mode (SM) and proportional-integral (PI) controllers. The results of the simulation demonstrated that the recommended SM-ANN controller has good performance in terms of enhancing the quality of energy that is delivered to the power network. This is in comparison to the traditional SM and PI controllers, which both have a long history of use. Notwithstanding the fact that there is DFIG parameter fluctuation present.

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“…Wind energy is one of the most frequently applied methods of power generation among the many different types of renewable energy resources because of its financial benefits and compatibility with power grids in many locations [1]. To improve the performance of wind power generation, researchers from the industrial and academic sectors have recently devoted their efforts to it [2]- [4].…”

Section: Introductionmentioning

confidence: 99%

Direct Field Orientation Control Based on H∞ Method of Wind Turbine Based on DFIG

Bakou

Saihi

Abid

et al. 2022

AJRESD

Self Cite

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This study aims to propose the direct field orientation control based on the H-infinity method (DFOC_ H∞) scheme for controlling the stator power (active/ reactive) of a direct drive vertical axis wind turbine power system based on a doubly fed induction generator (DFIG). the sensitivity to parameters uncertainty of the machine presents the major drawback of the PI controller, in order to cope with this problem; the H-infinity method was used to solve it. The proposed controller H∞ is evaluated with Matlab/Simulink. Simulation results showed that the suggested H∞ controller has a good performance in terms of enhancing the quality of energy provided to the power network. Even in the presence of DFIG parameter variation.

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Hybrid control based on sliding mode fuzzy of DFIG power associated WECS

Cited by 19 publications

References 9 publications

Sensorless passivity based control of doubly-fed induction generators in variable-speed wind turbine systems based on high gain observer

Sensorless passivity based control of doubly-fed induction generators in variable-speed wind turbine systems based on high gain observer

Hybrid sliding neural network controller of a direct driven vertical axis wind turbine

Direct Field Orientation Control Based on H∞ Method of Wind Turbine Based on DFIG

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