DFIG-based Wind Turbine Research Articles

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Tracking performance and power quality enhancement of DFIG based wind turbine using robust integral terminal sliding mode control

The aim of this work is to develop a robust Integral Terminal Sliding Mode Control (ITSMC) strategy for a Doubly Fed Induction Generator (DFIG) wind turbine (WT) operating in challenging conditions. This controller is designed to manage the system's rotor side converter (RSC) and grid side converter (GSC), ensuring maximum power production, improved power quality, and accurate tracking of system state variables, even in the face of fluctuating wind conditions, parameter uncertainties, and external disturbances. The stability of the proposed controller is assured using the Lyapunov theory. The performance of ITSMC is compared with that of the conventional sliding mode controller (SMC) and backstepping controller through simulation tests, using the integral absolute error (IAE) as a performance metric. The results highlight the superiority of ITSMC, demonstrating its ability to precisely track reference values, eliminate static errors, and minimize chattering. ITSMC consistently achieves the lowest IAE for all tracked state variables and across all test scenarios. A comparative study analyzing the Total Harmonic Distortion (THD) of the proposed controller versus SMC, the backstepping controller, and other similar works in the literature shows a marked improvement in the THD of stator and filter currents by at least 24.53 % and 7.96 %, respectively. These findings underscore the controller's capability to enhance the power quality delivered to the grid.

Fuzzy logic based improved direct torque control of DFIG-based wind turbines

This paper investigates direct torque control with a fuzzy controller (F-DTC) for a two-level voltage source inverter feeding the rotor of a doubly-fed induction generator (DFIG) based on a variable-speed wind energy conversion system (VSWECS). The wind turbine's MPPT technology is used to obtain the torque reference. The proposed fuzzy logic-based direct torque control (F-DTC) is designed to eliminate the flux and electromagnetic torque ripples that are common with existing (DTC) controls, leading to smoother operation and improved efficiency in the wind energy conversion system. The fuzzy logic controller improves switching decision-making by handling uncertainties and non-linearities, resulting in smoother and more efficient control of the torque and flux. To validate the effectiveness of the proposed F-DTC method, simulations are conducted in MATLAB/SIMULINK, and the results are compared with those of the classical DTC approach. The findings demonstrate that the F-DTC strategy significantly reduces torque and flux ripples, enhances the dynamic response, and improves overall system performance.

Using the proportional dual integral strategy to improve the characteristics of the indirect field-oriented control of DFIG-based wind turbine systems

In this work, a new indirect field-oriented command (IFOC) for wind systems based on a doubly-fed induction generator (DFIG) is designed to get better energy and stream quality. Also, overcoming the problems of IFOC. It is proposed to use proportional dual integral (PDI) controllers in order to replace traditional controllers and augment the robustness of the studied wind turbine system. The proposed IFOC-PDI is a modification of the IFOC, where the basic idea behind the designed technique is to combine a proportional-integral (PI) regulator with an integral term. This technique has been applied to the machine inverter, where the IFOC-PDI aims to calculate reference voltage values. The pulse width modulation (PWM) is used to translate voltage reference values ​​into pulses to run the machine inverter. The main objective of this article is to compare the competence of the IFOC-PDI to that of the IFOC-PI in different tests, including two different wind speed profiles and DFIG parameters variation. The major benefit of this command is a decrease in harmonic distortion of the currents, and active and reactive power (Ps and Qs) fluctuations. The results using MATLAB demonstrated that the IFOC-PDI improved the IFOC-PI in the minimization of stream harmonic distortion (6.63%, 10.42%, and 17.86%) and notable minimization of fluctuations in both Ps (32.08%, 46.24%, and 12.10%) and Qs (45.95%, 66.88%, and 14.49%). Also, the overshoot value of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 57.79%, 12.41%, and 33.96%. The steady-state error of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 29.43%, 85.88%, and 76.36%. The IFOC-PDI is also very resistant in the case of DFIG parameters variation.

Adaptive passive fault tolerant control of DFIG-based wind turbine using a self-tuning fractional integral sliding mode control

Controlling variable wind speed turbine (VWT) system based on a doubly-fed induction generator (DFIG) is a challenging task. It requires a control law that is both adaptable and robust enough to handle the complex dynamics of the closed control loop system. Sliding mode control (SMC) is a robust control technology that has shown good performance when employed as a passive fault-tolerant control for wind energy systems. To improve the closed control loop of VWT based on DFIG with the aim of improving energy efficiency, even in presence of nonlinearities and a certain range of bounded parametric uncertainties, whether electrically or mechanically, an adaptive passive fault tolerant control (AP-FTC) based on a self-tuning fractional integral sliding mode control law (ST-FISMC) developed from a novel hyperbolic fractional surface is proposed in this paper. ST-FISMC introduces a nonlinear hyperbolic function into the sliding manifold for self-tuning adaptation of control law, while fractional integral of the control law smooths discontinuous sign function to reduce chattering. Additionally, this work introduces an adaptive observer, developed and proved based on a chosen Lyapunov function. This observer is designed to estimate variations in electrical parameters and stator flux, ensuring sensorless decoupling in indirect field- oriented control (SI-FOC) of DFIG. Lyapunov theory is also used to prove stability of states vectors in closed control loop with presence of bounded parameters uncertainties or external disturbances. Simulation results show that the proposed approach offers better performance in capturing optimal wind energy, as well as the ability to regulate active/reactive power and high resilience in presence of occurring parameter uncertainties or external disturbances.

Disturbance observer-based finite-time adaptive neural control scheme of DFIG-wind turbine

This paper introduces a novel disturbance observer-based finite-time adaptive neural control approach to optimize wind power conversion in a doubly fed induction generator-based wind turbines (DFIG-WT). This control strategy offers appealing features including rapid finite-time convergence, both transient and steady-state performance enhancements, and robustness against external disturbances and inherent model uncertainties. The control strategy integrates the neural networks estimation capability with the interesting proprieties of the finite-time control method to achieve efficient wind power conversion. Closed-loop finite-time stability is conducted using the finite-time Lyapunov stability concept of nonlinear systems. The developed control strategy’s effectiveness is confirmed through numerical simulation.

FRT Capability Enhancement of DFIG-based Wind Turbine with Coordination Control of MSVC and FCL

Objective: To address the problems of various FRT (fault ride through) schemes in DFIG (doubly fed induction generator) systems, especially their applicability under different voltage sags, a combination scheme of an MSVC (minimized series voltage compensator) and FCL (fault current limiter) is proposed. Methods: Based on the analysis of the mathematical model of the DFIG and considering the capacity and volume in the process of practical engineering, the application structure and specific control strategy of an MSVC in DFIG systems are designed on the stator side, and the application effect is analyzed theoretically. Simultaneously, the application structure and control strategy of the FCL is proposed on the rotor side, and the application effect of the combination scheme is theoretically deduced and analyzed. Moreover, the simulation model is built on the MATLAB/Simulink platform. Results: The simulation results show that the scheme can quickly and effectively recover the fault voltage of the DFIG under different voltage sag degrees and has better dynamic performance. At the same time, it can effectively limit the fault current and suppress the DC-link voltage of the rotor side, and the transition process is relatively stable. Conclusion: The purpose of improving the FRT capability of the DFIG system is realized.

IoT based monitoring system for DFIG based wind turbines under voltage dips

Due to their partial-rating power converters and dynamic performance, doubly-fed induction generators (DFIGs) are commonly used in wind turbines (WT). However, grid-connected DFIGs are vulnerable to voltage dips, which can cause power quality concerns and possible turbine damage. An Internet of Things (IoT)-based monitoring technique for field-oriented control (FOC)-based DFIG with grid-side converter (GSC) control is proposed in this paper. The proposed approach uses real-time WT voltage and current data to dynamically alter the GSC control settings, allowing for steady operation and minimizing power quality problems during voltage dips. A 2 MW variable-speed pitch-controlled DFIG with a speed limit of 900–2000 rpm is used for performance investigation under voltage dips with crowbar protection. An IoT based monitoring system sends real-time information to a cloud server for additional analysis after detecting anomalies. The ThingSpeak cloud platform sends email notifications of defects, and an MIT App Inventor application is constructed for data visualization. The proposed strategy's effectiveness is confirmed through the simulation results.

Novel chattering free binomial hyperbolic sliding mode controller for asymmetric cascaded E-type bonded T-type multilevel inverter-based dynamic voltage restorer to meliorate FRT capability of DFIG-based wind turbine

The endurance capability of Doubly Fed Induction Generator (DFIG)-based wind turbine to network against different disturbances is an important criterion to meet the recent grid codes requirements. This generator has to provide the required energy under the perturbation conditions which is principally specified by Fault Ride-Through (FRT) capability. It refers to safe and continuous operation of DFIG without interruption which has been performed by Dynamic Voltage Restorer (DVR) using fast and accurate compensation of the voltage fluctuations. This paper aims to introduce an innovative quasi-sinusoidal voltage synthesizer for DVR to enhance the power quality and power delivery. Hence, a new Asymmetric Cascaded E-type Bonded T-type Multilevel Inverter (ACEBTMI) with binary geometric progression form of DC sources is proposed to provide high-step staircase sinusoidal voltage containing low semiconductor switches. Then, accurate triggering signals for the suggested ACEBTMI corresponding to the voltage fluctuations have been provided by new Chattering Free Binomial Hyperbolic Sliding Mode Controller (CFBHSMC). To validate compensation capability of the proposed DVR, ACEBTMI part has been compared with some traditional and familiar multilevel inverters, and also CFBHSMC part has been compared with SMC, FLC and PID controllers. In precise, the simulation results have definitely confirmed the accurate tracking and robust control performance of CFBHSMC to support ACEBTMI-based DVR which enables DFIG to ride-through different voltage perturbations.

Advanced Control Solutions for DFIG Wind Turbines: From Vector to Predictive Control

This paper investigates advanced control strategies for a doubly-fed induction generator-based wind turbine (DFIG-WT), focusing on vector control and model predictive control (MPC). Initially, it introduces the DFIG-WT structure and general control methods, then explores vector control for effective decoupled power management of active and reactive power. Despite vector control's efficiency, its limitations in handling constraints are highlighted, leading to the adoption of MPC. The study examines MPC's application in current control for three-phase two-level converters, showing its capability for fast tracking and response. Further, it explores MPC's model predictive torque control, demonstrating its proficiency in handling various requirements through a well-designed cost function. Overall, this research emphasizes MPC's adaptability and efficiency in optimizing DFIG-WT performance under varying operational conditions.

Estimating the region of attraction of wind integrated power systems based on improved expanding interior algorithm

AbstractThis paper proposes an improved expanding interior algorithm (EIA) to estimate the region of attraction (ROA) of power systems with wind power generation based on sum of squares (SOS) programming. An ordinary differential equation (ODE) model is derived for the doubly‐fed induction generator‐based wind turbine (DFIGWT), which is named as an enhanced synchronous‐generator‐mimicking (ESGM) model. The ESGM model bridges the gap between the requirement of an ODE model in ROA estimation and the conventional differential‐algebraic equation (DAE) model of the DFIGWT system. The ESGM model is able to accurately reflect the low frequency dynamics of the DFIGWT. Moreover, an improved EIA is designed to estimate the ROA based on SOS programming, which has higher efficiency than the existing ROA estimation algorithms based on SOS programming. It is able to adaptively search for the Lyapunov function and obtain an optimal estimation of the ROA in an iterative process. The accuracy and efficiency of this algorithm are verified in three test systems composed of DFIGWTs and synchronous generators (SGs). The morphological changes in the ROA of the test systems caused by the penetration of DFIGWT are examined.

Enhancing grid stability: a hybrid control strategy for DFIG-based wind turbines to mitigate sub-synchronous oscillations

Enhancing grid stability: a hybrid control strategy for DFIG-based wind turbines to mitigate sub-synchronous oscillations

Hardware-in-the-loop simulation to validate the fractional-order neuro-fuzzy power control of variable-speed dual-rotor wind turbine systems

New and efficient command strategies and algorithms are needed in the field of wind turbine energy generation to ensure power quality according to international standards. However, conventional linear strategies are still used to command doubly-fed induction generators (DFIGs). Thus, inadequate power quality is obtained, which can cause network-level disturbances. This Hardware-in-the loop (HIL) study presents a new command scheme for a DFIG-based dual-rotor wind turbine (DRWT) system. The new command is a combination of a neuro-fuzzy algorithm and fractional-order control that overcomes the declining power quality of the DFIG-DRWT system. The new strategy is based on using pulse width modulation to generate command pulses for the rotor-side converter of DFIG. In the designed command system, the reference value of the active power is determined using maximum power point tracking to provide efficient power conversion performance under different operating conditions. First, MATLAB software is used to implement the fractional-order neuro-fuzzy (FONF) control technique, and the behavior of the proposed strategy is studied in comparison to that of the traditional direct power command (DPC) technique. A comparison is performed in terms of the ripple minimization ratio, durability, overshoot, steady-state error, reference tracking, and current quality. The results of the comparison show the high performance of the FONF technique. Second, the FONF technique is implemented in HIL test using the dSPACE 1104 Card, where two different forms of wind speed are used to study the characteristics of the proposed strategy and confirm its effectiveness and performance in HIL test compared to DPC technique. The experimental results obtained in the two tests confirm the efficiency, effectiveness, and high performance of the proposed FONF technique compared to DPC technique in improving the energy system characteristics, and the simulation obtains the same results.

Decoupled feed-forward control model enhancement for low voltage ride through capability in DFIG-based wind turbines

Decoupled feed-forward control model enhancement for low voltage ride through capability in DFIG-based wind turbines

Analysis and Mitigation of Electromechanical Oscillations in Drivetrain for Hybrid Synchronization Control of DFIG-Based Wind Turbines

Analysis and Mitigation of Electromechanical Oscillations in Drivetrain for Hybrid Synchronization Control of DFIG-Based Wind Turbines

Simplified Transient Model of DFIG Wind Turbine for COI Frequency Dynamics and Frequency Spatial Variation Analysis

Simplified Transient Model of DFIG Wind Turbine for COI Frequency Dynamics and Frequency Spatial Variation Analysis

An emotional control approach to grid-connected DFIG based wind turbine

An emotional control approach to grid-connected DFIG based wind turbine

Robust Diagnosis of Multiple Open-Circuit Faults in DFIG Wind Turbines in Both Sub- and Super-Synchronous Operating Modes

Robust Diagnosis of Multiple Open-Circuit Faults in DFIG Wind Turbines in Both Sub- and Super-Synchronous Operating Modes

Passivity and higher-order sliding mode control for doubly-fed induction generation wind power system

To simplify the model of DGIG and improve the robustness, the variable speed and constant frequency (VSCF) DFIG wind power generation systems from the perspective of energy and robustness were studied. It was based on passivity and sliding mode control (SMC) theory. Firstly, the model of DFIG based on Euler-Lagrange (EL) equations was established, so the original DFIG wind turbine system is divided into electrical and mechanical subsystems. For two subsystems, the electrical subsystem was designed. In contrast, the mechanical subsystem is an energy-consuming system and is stable through selecting suitable design parameters. Hence, the system control algorithm is simplified. A high-order terminal SMC was designed to get a faster speed and better robustness for the speed loop. Simulation results show that the proposed controller is simple and effective. It can guarantee the wind power system outputs constant frequency. The motor speed can also track the reference speed quickly, so the performance of the wind turbine system is improved.

Computationally Efficient Reduced Order Modeling of DFIG-Based Wind Turbines: A Novel Frequency-Weighted and Limited Model Reduction Approach With Error Bounds

Computationally Efficient Reduced Order Modeling of DFIG-Based Wind Turbines: A Novel Frequency-Weighted and Limited Model Reduction Approach With Error Bounds