Doubly Fed Induction Generator Research Articles

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

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

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

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.

Wind Power Frequency Control in Doubly FED Induction Generator Using CFMPC-FOPID Controller Scheme

Because the majority of wind turbines operate in maximum output power tracking mode, power system frequency cannot be supported. However, if the penetration rate of wind power increases, the system inertia related to frequency modulation may decrease. In addition, frequency stability will be severely affected in the event of significant disturbances to the system load. Due to the high penetration of wind power in isolated power systems, this study suggests a coordinated frequency management approach for emergency frequency regulation. In order to prevent the phenomenon of load frequency control in doubly fed induction generators (DFIGs), a unique efficient control scheme is developed. The Cascaded Fractional Model Predictive Controller coupled with Fractional-Order PID controller (CFMPC-FOPID) is developed to provide the DFIG system with an efficient reaction to changes in load and system parameters. The proposed controller must have a robust tendency to respond quickly in terms of minimum settling time, undershoot, and overshoot. Nonlinear feedback controllers are designed using frequency deviations and power imbalances to achieve the reserve power distribution between generators and DFIGs in a variety of wind speed conditions. It makes upgrading quick and easy. In Matlab/Simulink, a simulation model is built to test the viability of the suggested approach.

Current source converter-based optimal power extraction and power control of a doubly fed induction generator (DFIG) using backstepping control

An improved backstepping control technique for the operation of a doubly fed induction generator (DFIG) powered by a wind turbine (WT) was developed and discussed. It is derived from a current source converter (CSC). The optimal backstepping control (BSC) settings are determined using the CSC approach, which can improve the drive by providing a more rapid dynamic response, greater precision, and stable performance. The CSC approach control function was constructed using the index criterion integral time square error (ITSE) and integral time absolute error (ITAE). With the simulation technique in the MATLAB/Simulink environment, the proposed BSC-CSC effectiveness is confirmed, and analyse the performance by using the PI and SMC control. The results indicate the goals of this work have been achieved in the form of resilience, improved dynamic system efficiency, lowering the harmonic distortion, optimization of stator power, and successfully addressing the problem of model parameter uncertainty.

Recovery time and strategy of DFIG speed based on a high-proportional hydropower grid

Large-scale wind power access reduces the equivalent inertia of a power system. The wind turbine has a considerable reserve of rotational inertia, which is important for reducing the risk of low-inertia operation in a grid and for improving frequency reliability. In this work, a doubly fed induction generator (DFIG) inertia frequency regulation strategy is studied. The secondary dip in frequency caused by speed recovery after the wind turbine participates in frequency regulation is an important factor that limits regulation capability on the DFIG. To address such problem, the power dip and recovery generated by the DFIG after active speed recovery is analyzed and modeled. Then, a linearized frequency response model of a hydropower single machine is established to investigate the secondary disturbance effect of wind turbine active speed recovery moment on the frequency of the high-ratio hydropower system.A conclusion is drawn that the moment that corresponds to the first recovery of system frequency to the quasi-steady-state frequency is the optimal recovery moment of the turbine in the linear SFR model. Combined with the frequency control characteristics of the frequency limit control(FLC)’s “large dead zone, ” an active speed recovery strategy of the turbine based on frequency deviation judgment is designed.

Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator

Recently, deep learning has provided a new opportunity to achieve high precision and real-time parameter identification of the doubly-fed induction generator (DFIG) in the event of short-circuit fault. However, deep learning algorithms based on data training are facing the challenge of relying on a large amount of training data and poor generalization performance. In order to improve these shortcomings, we embed the forward calculation model of three-phase short-circuit current (SCC) into the neural network, and propose an unsupervised neural network which can realize high-precision parameter identification. The network only needs to convert the short circuit current curve into a two-dimensional gray level map to complete the precise training of the network without real labels, which effectively improves the fitting ability of the network for inverse problems. The simulation results show that the proposed method can achieve high precision identification of DFIG parameters both within and outside the domain, and verify the high precision identification and generalization ability of unsupervised networks.

Supervisory control of reactive power in wind farms with doubly fed induction generator-based wind turbines for voltage regulation and power losses reduction

This paper proposes a strategy based on the secondary voltage control (SVC) and the use of grid codes recommended by the system operator to determine the reactive power reference value between a wind farm (WF) with doubly-fed induction generator (DFIG) and the electrical grid. The proposed strategy seeks to determine the reactive power reference value required of WF during normal operating and grid faults. When the voltage deviation is within the normal range, the proposed strategy maintains a unity power factor (UPF). If the voltage deviation exceeds the normal range, it provides reactive power compensation to ensure voltage stability. To achieve this objective, the proposed strategy is compared with the SVC. This strategy can reduce the size of potential compensation devices, such as static synchronous compensators, to be used to improve the WF response, if needed. The participation of the grid converter side (GSC) in the reactive power control allows the DFIG to reduce power losses and increases the life of the converters, especially the rotor converter side (RSC). The strategy proposed in this work is implemented on Matlab/Simulink using the S-Function builder to evaluate their performance, which facilitates its integration into real control boards and testing in real experiments in the future.

An Effective SST-FLC for Mitigation of Reactive Power Compensation of DFIG Based Wind Energy Conversion System

As wind-derived energy is increasingly incorporated into interconnected energy networks, this research attempts to control reactive power and regulates the voltages of wind energies. Since wind energy is volatile, it will generate unstable power and voltages. The reactive powers control of wind energy and faults on the grid is becoming more essential. One of a power system’s most crucial characteristics, it has a big impact on the stability of the whole thing. In terms of high-switching-frequency energy electronics generators, solid-state transformers (SST) may perform reactive power correction in WFs. The solid-state transformers suggested here connect wind farms powered by double-fed induction generators to the grids in place of energy transformers with real controllers in a conventional arrangement. The dual-active bridge converters and fuzzy logic controllers are both built into the solid-state transformers architecture. Power transmission between both sources of power can be accomplished using bidirectional DC–DC converters in either way. Modernized grid applications are the most promising ones for solid state transformers and increase the efficiency up to 96.61% with 0.91 Power factor of the entire power generation system with bit error rate of 0.2%. This will reduce the cost, improves the system’s efficiency, and also improves the system’s performance.

Multi-Objective PSO for Control-Loop Tuning of DFIG Wind Turbines with Chopper Protection and Reactive-Current Injection

The control systems for the variable-speed wind turbine based on the Doubly Fed Induction Generator (DFIG) pose some tuning challenges. The performance and stability of DFIG wind turbines during faults in power grids are directly related to their controller settings. This work investigates how incorporating protection via a braking-Chopper controller connected to the DC link (DC Chopper) and a reactive-current injection during the PI-tuning process affects the performance of DFIG wind turbines during electrical faults. For the tuning process, the Multi-Objective-Particle-Swarm-Optimization (MOPSO) algorithm was used. Thus, two different approaches adopting this methodology were investigated, considering sequential and simultaneous tuning. The results showed that sequential tuning presented a better performance in relation to the reactive-current injection and lower amplitude deviations of the electrical quantities during and after the fault. On the other hand, simultaneous tuning reached damping of the mechanical oscillations faster and presented better performance of the protection system.

Three-stage dynamic equivalent modeling approach for wind farm using accurate crowbar status identification and voltage differences among wind turbines

With increasing wind farm scale, dynamic modeling and simulating the low-voltage ride-through (LVRT) process of wind farms are time- and source-consuming. Thus, a dynamic equivalent model of a wind farm considering the LVRT process is necessary and vital for power system analysis. However, the crowbar status of each doubly-fed induction generator (DFIG), voltage, and wind speed differences among will influence the LVRT process and equivalent results. To consider these three factors comprehensively and eliminate the error, this paper proposes a three-stage dynamic equivalent modeling approach, using accurate crowbar identification and voltage differences among DFIGs. Stage I: DFIGs are divided by crowbar status. A new accurate crowbar identification method is proposed to consider the interference from other DFIGs, using the experimental two-machine system and several dynamic simulations to correct fault voltage. Stage II: The often-overlooked voltage differences are considered, and DFIGs are divided into different clusters for accurate fault dynamics. Stage III: To eliminate errors resulting from wind speed differences, the DFIG active power reference is corrected based on the analytical function of the wind farm LVRT process. The proposed model can accurately identify crowbar status and consider the voltage and wind speed differences without detailed model simulation results, improving the accuracy. Case studies are undertaken on a wind farm with fifty DFIGs. Simulation results indicated that the proposed model can match the detailed model under different wind scenarios and fault voltages, and it also increases simulation efficiency, which is suitable for studying the effect of LVRT on power systems.