Doubly Fed Induction Generator Research Articles

ANN-PI Controller for the Grid-Side Converters in Wind Energy Conversions Systems under Voltage Dips

Standard electrical network codes require wind power systems to maintain the supply of active and reactive power, even in the event of operating conditions being disrupted. This paper presents a new controller for the grid side converter (GSC) in a wind power system based on a doubly fed induction generator (DFIG). This controller integrates a neural network, which adjusts the parameters of a PI regulator in real time. This enables the wind system to adapt to varying operating conditions. The control objectives are twofold: (i) regulating the DC bus voltage through the control of the injected grid current quadratic component; and (ii) regulating the reactive power transmitted to the grid, through the control of the injected grid current direct component. The reactive power control allows the wind system power factor (PFC) to be adjusted. To highlight the interest of the proposed controller, these performances are compared to that of a controller based on conventional PI regulators. The simulations presented here were conducted in Matlab/Simulink and demonstrate the enhanced performance of the proposed controller.

Control Strategies of DFIG Technology-based Variable-Speed Wind Turbines-A Review

This review paper examines the advancements and limitations of wind energy technology, while concentrating on the utilization of Doubly Fed Induction Generators (DFIG) to capture maximum power in variable speed winds. The paper evaluates the efficacy of several control strategies for DFIG relying on WT (wind turbines), on the basis of their simulation results, key features, and control objectives. The paper highlights the potential areas for investigation to improvise the performance as well as efficiency of wind energy generation.

Comparative Analysis of Low Voltage Ride Through Techniques of DFIG Connected to Grid using AI Techniques

The requirement for clean and eco-friendly energy initiated the production of renewable energy. Wind energy promises attractive features such as bulk power production and reduced maintenance cost. Advancement of technologies in the field of wind turbines and generators made the gates open for attractive investments. Adjustable-speed wind turbines tied to Doubly Fed Induction Generators (DFIG) became the most excellent choice of power utilities due to their low-cost power converters and four-quadrant control of useful and wattless powers. The ability to extract a high amount of power for a specified wind speed is a major advantage of DFIG which attracted Power system Operators (PSOs). Low voltage ride-through and wattless Spower support to the grid are estimated and compared using conventional PI controllers, Artificial Neural Network (ANN), and Random Forest Optimization (RFO) algorithm.

Optimal Control of Brushless Doubly Fed Wind Power Generator under Zero-Voltage Ride-Through

In the grid-connected operation dynamics of brushless doubly fed generators (BDFGs), a dip in the grid voltage is equivalent to suddenly adding a reverse voltage source at the parallel node. By deriving the expressions of the transient current of power winding (PW), control winding (CW), and rotor winding (RW) of a BDFG in the complex frequency domain under a natural state, it was concluded that the overshoot and oscillation time are affected by the CW voltage, the drop degree and phase of the grid voltage, and the rotor speed. Therefore, an optimal control strategy is proposed. A state model with the CW current as the state variable was constructed using the Pontryagin minimum principle. The finite-time integral value of the square of the electromagnetic torque was set as the objective function to achieve the minimum value that could suppress the overshoot and oscillation of the electromagnetic torque, and the optimal CW voltage command value was directly solved to accelerate the convergence of the BDFG’s physical quantities, thereby reducing the amplitude. Finally, the feasibility of the optimal control algorithm was verified using tests on an experimental platform.

Reduced-Order Model for Wind-Solar Multi-Microgrids Considering Time-Scale Coupling

A computationally efficient and accurate reduced-order model (ROM) that characterizes the time-scale coupling caused by the high penetration of power-electronic converters in microgrids (MGs) is crucial to system stability analysis. When such MGs are interconnected into multi-microgrids (MMGs), the coupling between fast and slow dynamics will be more complicated due to the interactions among each MG. The traditional ROM without concerning dynamic coupling may lead to low accuracy and even misjudgment of system stability. In this paper, by considering primary energy dynamics of renewable energy sources, e.g., doubly-fed induction generator (DFIG) and photovoltaic (PV), a small-signal model that characterizes the practical multi-timescale of MMGs is firstly presented. Then with the division of the entire MMGs into fast and slow dynamic subsystems based on the assumption of time-scale separating, the coupling dynamics are identified via the residues-based method. Finally, a ROM considering coupling dynamics and preserving physical meaning is proposed by reconfiguring the fast and slow dynamic subsystems based on singular perturbation. The accuracy of the proposed ROM is verified by comparing it with the detailed model under different control parameters, wind speeds and irradiance conditions. The time-domain simulation is employed to validate the dynamic response of the proposed ROM.

Doubly-Fed Induction Generator with Hybrid Renewable Sources

Doubly-Fed Induction Generator with Hybrid Renewable Sources

Comprehensive Approach to Enhance the Output Power of DFIG-Based Wind Energy Conversion Systems

This paper presents a method for measuring a wind turbine's MPP (Maximum Power Point) with a three-bladed VSWT that is driven by a DFIG (Double-Fed Induction Generator) (Variable Speed Wind Turbine). The rotor incorporates a DFIG with successive PWM voltage-source converters within its integrated rotor integrated circuit. Grid-side converters generate and establish sinusoidal currents while independently managing the active and reactive power drawn from the grid supply using vector control techniques. The rotor-side converter needs to be vector controlled in order for the speed range to function. The vector approach manages the permit circuit optimally to maximize the amount of wind energy gathered. The control needs of the permit circuit take this into account. Such a system is analyzed using MATLAB software

A novel HOSMO-based Rotor Speed estimating strategy for DFIG-based Wind Turbines

In this paper, a novel rotor speed estimation technique based on a high-order sliding mode observer (HOSMO) for a doubly-fed induction generator (DFIG) used in variable speed wind turbines (VSWT) is presented. The novelty of this observer lies under the suggestion that only the rotor currents are measured instead of measuring both stator and rotor currents. This decrease the uncertainties implemented by physical sensors, and reduce the measurement error probability that is not tolerated in control systems. Furthermore, the investment and maintenance costs will be lower. This observer demonstrated high performance through the simulations conducted in Matlab/Simulink software.

Modeling and Chaos Dynamics Analysis of Doubly-Fed Induction Generator Based on Incommensurate Fractional-Order

Modeling and Chaos Dynamics Analysis of Doubly-Fed Induction Generator Based on Incommensurate Fractional-Order

Arc Fault Diagnosis Method for Brush Slip Ring System of Doubly-Fed Induction Generator Based on Image Recognition

Arc Fault Diagnosis Method for Brush Slip Ring System of Doubly-Fed Induction Generator Based on Image Recognition

Performance analysis of doubly-fed induction generator using PID controller optimised by whale optimisation

Performance analysis of doubly-fed induction generator using PID controller optimised by whale optimisation

Stability Analysis and Enhanced Virtual Synchronous Control for Brushless Doubly-fed Induction Generator Based Wind Turbines

Stability Analysis and Enhanced Virtual Synchronous Control for Brushless Doubly-fed Induction Generator Based Wind Turbines

Primary Frequency Reserve Providing Strategy of Doubly-Fed Induction Generator Wind Generation Using Rotor Inertia Characteristics

Primary Frequency Reserve Providing Strategy of Doubly-Fed Induction Generator Wind Generation Using Rotor Inertia Characteristics

Real-time Neural Sliding Mode Linearization Control for a Doubly Fed Induction Generator under Disturbances

Abstract This paper presents an experimental implementation of a Neural Sliding Mode Linearization approach for the control of a double-fed induction generator connected to an infinite bus via transmission lines. The rotor windings are connected to the grid via a back-to-back converter, while the stator windings are directly coupled to the network. The chosen control scheme is applied to obtain the required stator power trajectories by controlling the rotor currents and to track the desired values of the DC-link output voltage and the grid power factor. This controller is based on a neural identifier trained online using an Extended Kalman Filter. Based on such identifier, an adequate model is obtained, which is used for synthesizing the required controllers. The proposed control scheme is experimentally verified on 1/4 HP DFIG prototype considering normal and abnormal grid conditions. In addition, maximum power extraction from a random wind profile is tested in the presence of different grid scenarios. Moreover, a comparison with conventional control schemes is performed. The obtained results illustrate the capability of the proposed control scheme to achieve active power, reactive power, and DC voltage desired trajectories tracking and to operate the wind power system even in the presence of parameter variation and grid disturbances, which helps to ensure the stability of the system and improve generated power quality.

Feedback Control of Doubly-Fed Generator Connected to Current Source Converter

Feedback Control of Doubly-Fed Generator Connected to Current Source Converter

Comparative study between PI, FLC, SMC and Fuzzy sliding mode controllers of DFIG wind turbine

In speed control, double-fed-induction generator (DFIG) has attracted attention in wind energy conversion systems (WECs). These systems can offer higher performances by controlling converters that connect the generator windings to the grid network. Therefore, different control strategies have been used. We can find the proportional integral (PI) and sliding mode control (SMC) which offer better performances. However, PI has constant gains that can’t change with the external variation and SMC has a chattering problem. Therefore, a hybrid control system that combines fuzzy logic control (FLC) and SMC to perform fuzzy sliding mode control (FSMC) is proposed. The hybrid system can improve the FLC and SMC robustness. The DFIG modeling and each of the control strategies have been detailed. To demonstrate the effectiveness of the control strategies, a comparative study of different control strategies (PI, FLC, SMC and FSMC) is described and performed using MATLAB/Simulink software. The results obtained from the present study show that FSMC is more robust and efficient than the other controllers (PI, FLC and SMC). It has high performances (low settling time, high steady state accuracy) assuring a perfect power decoupling with minimal ripples and errors.

Power Quality Gain of Self-Lift Luo Converter used for Hybrid Renewable Power System with Battery Grid Integration

The renewable power sources such as wind as well as photovoltaic (PV) energy are fashionable for residential and commercial applications. For the reason, that eco friendlessness plus expenditure are effective. This paper intends a Self-Lift Luo converter integrated with solar photovoltaic system to the utility grid along with its Adaptive Neuro-Fuzzy Inference System (ANFIS) and Recurrent Neural Network (RNN) control strategies are proposed. By achieve an energy management for the proposed system using Bidirectional Battery converter along with battery system. Power supervision move towards is suggested to control the DC bus voltage by way of Self-Lift Luo converter. The wind power with Doubly Fed Induction Generator (DFIG) based grid integration with a PI controller. Under this work, DSTATCOM has been used to improve the quality of power under different load conditions. The obtained results designate that the proposed approach delivers recovered performance with enhanced efficiency and nominal harmonics. The intact system is validated through a MATLAB simulation.

Modelling of Variable Speed Wind Turbine Connected DFIG:250KW

This manuscript initiates the design and analysis of a doubly-fed-induction-generator (DFIG) linked to the grid, aiming to assess a wind vitality conversion configuration employing an emulated wind turbine drive system. The generator’s configuration involves integrating the d-q axes reference framework with the stator flux. Independent management of real, and imaginary power, along with the dc-bus potential at the grid, is achieved through the field-aligned regulating method. Controlling real, and Quadrature power, as well as DC-bus potential, is executed using tandem converters at distinct velocities, encompassing sub, syn, and hyper-synchronous speeds. The effectiveness of these control strategies is validated through the emulation of a variable-speed wind turbine-connected DFIG, showcasing precise control over DC voltage, reactive power, and active power.

Optimization of the Powers Exchanged between a Cascaded Doubly Fed Induction Generator and the Grid with a Matrix Converter

The use of an electromagnetic converter of great reliability in wind energy, like the cascaded doubly fed induction generator (CDFIG), can solve several problems compared to the doubly fed induction generator (DFIG), among them the elimination of the brushes and copper rings. The work consists of studying the performance of a CDFIG-based wind system using a matrix converter and a variable pitch control system. The traditional PI is able to successfully solve a number of linear control problems. The fuzzy logic controller used can dramatically improve the system's performance. The active and reactive energy transferred between the CDFIG and the grid can be controlled by adjusting the machine inverter. The DC bus voltage has been kept stable by controlling the grid inverter. The pitch controller's objective is to maximise aerodynamic power while staying within the converter's power limits. Numerical simulation results implemented in the MATLAB/Simulink package will be provided in this study to show that the suggested control strategy is both possible and effective.

Generalized Predictive Control of the Active and Reactive Stator Powers of the DFIG for Wind Energy Generation

This paper proposes a Generalized Predictive Control (GPC) strategy for Wind Power Generation (WPG) based on a doubly fed induction generator (DFIG). The objective is to study and apply a robust active and reactive power control strategy based on GPC of the DFIG, this is likely to optimize the energy production and improve the quality of the energy produced. In order to maximize the amount of WPG taken even when the turbine is uncertain or the wind speed varies abruptly, the design is built utilizing the Maximum Power Point Tracking (MPPT) theory. Through numerical modeling with the aid of the Matlab/Simulink software, the predictive control (GPC) of the active and reactive stator powers of the DFIG was validated. A comparison between the GPC of the GADA and the indirect method based on a typical PI controller is developed in order to illustrate the viability of the suggested method. According to the simulation results of this comparison, the suggested method is viable and has promising results.