Robust Sliding Mode Control based MPPT for a PV/Wind Hybrid Energy System

Zebraoui, Otmane; Bouzi, Mostafa

doi:10.22266/ijies2018.1031.27

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…In order to improve the tracking efficiency the conventional algorithms are combined with nonlinear controller such as backstepping and sliding mode. In [7], the authors try to limit the chattering phenomena of sliding mode and to reduce the oscillations of perturb and observe loop. The proposed method which combines the two algorithms exhibits good convergence speed, but the main disadvantage is the oscillations remain around the maximum power point and the proposed algorithm.…”

Section: Introductionmentioning

confidence: 99%

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

2022

IJIES

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In this paper, in order to track the maximum power point under partial shading condition, An Artificial Neural Network based Particle Swarm Optimization (ANNPSO) combined with backstepping controller has been employed. The proposed controller relay to the ability of the PSO to find the global maximum power point and to the ANN to generate a reference voltage according to the PSO data without oscillations. The backstepping controller has been employed in order to track the reference voltage generated by the ANN by adjusting the duty cycle of the SEPIC converter. The simulation was carried out using MATLAB software. On one hand, the results affirms the ability of the proposed controller to find and to track the global maximum power point, and on the other hand the present method demonstrates high efficiency against previous works, The results shows that the proposed method tracks the reference voltage within 20 ms and it is able to tracks the GMPP with high performance. Furthermore, the experimental study shows that the proposed controller can be easily implemented using low coast materials, and the obtained results show a gain of 5W compared to the controller that combine the incremental conductance with backstepping.

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Section: Introductionmentioning

confidence: 99%

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

2022

IJIES

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“…On the other hand, The DFIG is an asynchronous generator equipped with a coil rotor, and its stator is linked to the electrical grid without the necessity of an additional power source, and the rotor is connected to the electrical grid via a pair of inverters, which are reversible static power frequency converters [3]. Using a control system for the converters can continuously optimize the power output by finding the point where the maximum power is produced [4].…”

Section: Introductionmentioning

confidence: 99%

Secures and maintains non-linear control of DFIG-wind turbine by implementing the appropriate protection configuration against overcurrent in the rotor circuit under grid fault

Loulijat,

El marghichi,

Abboud

2023

E3S Web of Conf.

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One significant disadvantage of the doubly fed induction generator (DFIG) is its high vulnerability to grid faults, which can be attributed to the direct linkage of its stator windings to the electrical network. The electromagnetic pairing of the stator and rotor in the DFIG implies that a voltage dip causing excessive stator current results in high currents in the sensitive back-to-back inverters and an overcharge in the DC-link capacitor. A comparative study of two protection configurations with a sliding mode non-linear control (SMC) for the rotor transient current for the better operation of the DFIG under network faults is presented in this document. One conventional configuration consists of a crowbar with DC-chopper and another is changed by adding to the crowbar an RL series device known as an appropriate protection configuration (APC). Both are placed within the rotor windings and ride-side converter (RSC) to achieve secures and maintains SMC of DFIG. The comparison of the results reached with the MATLAB/ SIMULINK application is evidenced by the success of these two configuration reduce the high rotor current and DC-link voltage. Additionally, the conventional configuration, in conjunction with the APC, diminishes the current RSC to levels below 0.2kA and exactly 2.25kA, while also being capable of absorbing up to 2.52kA and 1.3kA in the event of a grid fault. So the main difference is that with the APC, the decoupling of the RSC to the rotor in the presence of a fault can be averted, thereby assuring the control of all stator power via the RSC converte.

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“…In [6], Authors propose a maximum power point tracking controller for hybrid Photovoltaic -Wind energy system. The controller is developed by the combination of perturb & observe and Sliding Mode.…”

Section: Introductionmentioning

confidence: 99%

Fast and Efficient Maximum Power Point Tracking Controller for Photovoltaic Modules

Chennoufi¹,

Ferfra²

2020

Adv. sci. technol. eng. syst. j.

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This paper presents an efficient Maximum Power Point Tracking (MPPT) controller for photovoltaic modules. The MPPT technique consists of a combination between backstepping controller and artificial neural network (ANN).The (ANN) has been employed to generate the optimum voltage, which corresponds to the maximum power voltage delivered by photovoltaic modules, while the backstepping controller is developed to track the generated voltage, by computing the duty cycle of the Single Ended Primary Inductor Converter (SEPIC). The control of the boost converter is based on Lyapunov stability analysis, and an integral action is added to increase system robustness. In order to prove the accuracy of the developed control a comparison between the proposed method and sliding mode was carried out. In addition the stability was evaluated under sudden variation of environmental conditions. The simulation was carried out in MATLAB software, the results shows that the proposed controller tracks the reference voltage within 25 ms, in addition the systems reacts to sudden environments change with no oscillations, which demonstrate the robustness of the proposed method.

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Robust Sliding Mode Control based MPPT for a PV/Wind Hybrid Energy System

Cited by 11 publications

References 15 publications

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

Secures and maintains non-linear control of DFIG-wind turbine by implementing the appropriate protection configuration against overcurrent in the rotor circuit under grid fault

Fast and Efficient Maximum Power Point Tracking Controller for Photovoltaic Modules

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