Doubly-Fed Induction Generator Drive System Based on Maximum Power Curve Searching using Fuzzy Logic Controller

2015 ◽  
Vol 5 (4) ◽  
pp. 583
Author(s):  
Abdelhak Dida ◽  
Djilani Benattous
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Reactive Power ◽  
Maximum Power ◽  
Torque Control ◽  
Induction Generator ◽  
Main Function ◽  
Power Curve ◽  
Doubly Fed Induction Generator ◽  
Doubly Fed

This paper proposes a novel variable speed control algorithm for a grid connected doubly-fed induction generator (DFIG) system. The main objective is to track the maximum power curve characteristic by using an adaptive fuzzy logic controller, and to compare it with the conventional optimal torque control method for large inertia wind turbines. The role of the FLC is to adapt the transfer function of the harvested mechanical power controller according to the operating point in variable wind speed.  The control system has two sub-systems for the rotor side and the grid side converters (RSC, GSC). Active and reactive power control of the back-to-back converters has been achieved indirectly by controlling q-axis and d-axis current components. The main function of the RSC controllers is to track the maximum power through controlling the electromagnetic torque of the wind turbine. The GSC controls the DC-link voltage, and guarantees unity power factor between the GSC and the grid. The proposed system is developed and tested in MATLAB/SimPowerSystem (SPS) environment.

Intelligent Control for Doubly Fed Induction Generator Connected to the Electrical Network

2016 ◽  
Vol 7 (3) ◽  
pp. 688 ◽  
Author(s):  
Anass Bakouri ◽  
Hassane Mahmoudi ◽  
Ahmed Abbou
Keyword(s):  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Direct Torque Control ◽  
Torque Control ◽  
Electrical Network ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Intelligent Technique ◽  
Doubly Fed ◽  
Grid Side

<p><span lang="EN-US">In this paper we are interested in optimizing the wind power capture, using the Doubly Fed Induction Generator (DFIG). This machine is preferred to other types of variable speed generator because of their advantages in economic terms and control. The Artificial Neural Network (ANN) based on Direct Torque Control (DTC) which is used to control the electromagnetic torque in order to extract the maximum power, The  main  objective  of this intelligent technique is to replace the conventional switching table  by  a  voltage  selector  based  on  (ANN)  to  reduce torque  and  flux  ripples. Moreover, the fuzzy logic controller is used to grid side converter to keep DC link voltage constant, and also to achieve unity power factor operation. The main advantage of the two control strategies proposed in this paper is that they are not influenced by the variation of the machine parameter. The pitch control is also presented to limit the generator power at its rated value. Simulation results of 1,5 MW, for (DFIG) based Wind Energy Conversion System (WECS) confirm the effectiveness and the performance of the global proposed approaches.</span></p>

scholarly journals Doubly Fed Induction Generator Wind Turbines with Fuzzy Controller: A Survey

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
J. S. Sathiyanarayanan ◽  
A. Senthil Kumar
Keyword(s):  
Fuzzy Logic ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Fuzzy Logic Controller ◽  
Wind Farms ◽  
Voltage Regulation ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Doubly Fed

Wind energy is one of the extraordinary sources of renewable energy due to its clean character and free availability. With the increasing wind power penetration, the wind farms are directly influencing the power systems. The majority of wind farms are using variable speed wind turbines equipped with doubly fed induction generators (DFIG) due to their advantages over other wind turbine generators (WTGs). Therefore, the analysis of wind power dynamics with the DFIG wind turbines has become a very important research issue, especially during transient faults. This paper presents fuzzy logic control of doubly fed induction generator (DFIG) wind turbine in a sample power system. Fuzzy logic controller is applied to rotor side converter for active power control and voltage regulation of wind turbine.

Fuzzy Logic Based Control Scheme for Doubly Fed Induction Generator Based Wind Turbine

2018 ◽  
Vol 19 (6) ◽  
Author(s):  
Jawaharlal Bhukya ◽  
Vasundhara Mahajan
Keyword(s):  
Fuzzy Logic ◽  
Power Control ◽  
Wind Turbine ◽  
Reactive Power ◽  
Pi Controller ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Rapid Variation ◽  
Control Scheme ◽  
Doubly Fed

Abstract Stator Flux Orientation Control Scheme (SFOCS) has limitations that its performance is mainly influenced by the tuning of parameters, the Proportional-Integral (PI) controller could not compensate system variations very efficiently. To overcome the drawbacks of PI controller the Fuzzy Logic Controllers (FLCs) are modelled. This paper presents the fuzzy logic based control strategy for the variable speed wind turbine generator by using Doubly Fed Induction Generator (DFIG). The mathematical model for DFIG is developed in synchronous reference frame by using SFOCS for current and voltage control and is discretized in time domain. Based on this model the artificial intelligence based FLCs are designed and implemented so as to improve the performance and efficiency of the system. This control scheme not only enhances the dynamic performance but also maintains almost unity power factor to the grid. In order to explore the robustness of the FLC and conventional PI controller, simulations are carried out for rapid variation of wind speed, and different disturbances generated in the system. The simulation results show that the proposed fuzzy logic based control strategies have better power control, faster oscillation damping, more accurate regulation, considerably reduced settling time and has fewer ripples in comparison with conventional PI controller. In the proposed SFOCS, the PI controllers are replaced with FLCs, to improve the performance and efficiency of the system. The system performance is analyzed for real and reactive power control in SFOCS for the effectiveness of synchronization with the grid.

scholarly journals A Robust Interval Type-2 Fuzzy Logic Controller for Variable Speed Wind Turbines Based on a Doubly Fed Induction Generator

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 21
Author(s):  
Ahmed Vall Hemeyine ◽  
Ahmed Abbou ◽  
Anass Bakouri ◽  
Mohcine Mokhlis ◽  
Sidi Mohamed ould Mohamed El Moustapha
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Induction Generator ◽  
Great Success ◽  
Doubly Fed Induction Generator ◽  
Variable Speed ◽  
Doubly Fed ◽  
Interval Type

This paper presents an implementation of a new robust control strategy based on an interval type-2 fuzzy logic controller (IT2-FLC) applied to the wind energy conversion system (WECS). The wind generator used was a variable speed wind turbine based on a doubly fed induction generator (DFIG). Fuzzy logic concepts have been applied with great success in many applications worldwide. So far, the vast majority of systems have used type-1 fuzzy logic controllers. However, T1-FLC cannot handle the high level of uncertainty in systems (complex and non-linear systems). The amount of uncertainty in a system could be reduced by using type-2 fuzzy logic since it offers better capabilities to handle linguistic uncertainties by modeling vagueness and unreliability of information. A new concept based on an interval type-2 fuzzy logic controller (IT-2 FLC) was developed because of its uncertainty management capabilities. Both these control strategies were designed and their performances compared for the purpose of showing the control most efficient in terms of reference tracking and robustness. We made a comparison between the performance of the type-1 fuzzy logic controller (T1-FLC) and interval type-2 fuzzy logic controller (IT2-FLC). The simulation results clearly manifest the height robustness of the interval type-2 fuzzy logic controller in comparison to the T1-FLC in terms of rise time, settling time, and overshoot value. The simulations were realized by MATLAB/Simulink software.

Dynamic response improvement of doubly fed induction generator-based wind farm using fuzzy logic controller

2012 ◽  
Vol 63 (5) ◽  
pp. 281-288 ◽  
Author(s):  
Hany M. Hasanien ◽  
Essam A. Al-Ammar
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Response ◽  
Wind Farm ◽  
Fuzzy Logic Controller ◽  
Wind Farms ◽  
Normal Operation ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Simulation Results ◽  
Doubly Fed

Doubly fed induction generator (DFIG) based wind farm is today the most widely used concept. This paper presents dynamic response enhancement of DFIG based wind farm under remote fault conditions using the fuzzy logic controller. The goal of the work is to improve the dynamic response of DFIG based wind farm during and after the clearance of fault using the proposed controller. The stability of wind farm during and after the clearance of fault is investigated. The effectiveness of the fuzzy logic controller is then compared with that of a PI controller. The validity of the controllers in restoring the wind farms normal operation after the clearance of fault is illustrated by the simulation results which are carried out using MATLAB/SIMULINK. Simulation results are analyzed under different fault conditions.

scholarly journals Design and investigations of MPPT strategies for a wind energy conversion system based on doubly fed induction generator

2020 ◽  
Vol 10 (5) ◽  
pp. 4770 ◽  
Author(s):  
Bouchaib Rached ◽  
Mustapha Elharoussi ◽  
Elhassane Abdelmounim
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Conversion ◽  
Fuzzy Logic Controller ◽  
Maximum Power ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Doubly Fed

The purpose of this work is to design and to discuss various strategies to optimize the production of a wind energy conversion chain based on the doubly fed induction generator (DFIG), by capturing the maximum power at the wind turbine, using maximum power point tracking (MPPT) and pitch control. The proposed controls allow the generator to monitor the optimal operating points of the turbines regardless of wind speed variations, system parameters disturbance, and parameters variation. Simulation of WECS based on a 1.5 MW wound rotor induction generator under MATLAB/SIMULINK is carried out using the PI controller (PIC), RST controller and fuzzy logic controller (FLC). Analysis and comparisons are made for different operating scenarios: Reference tracking, robustness under variable wind speed conditions and parameters variation. The application of FLC provides a very interesting outcome for the robustness and the dynamic challenges.

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