Doubly Fed Induction Generator Wind Turbine Research Articles

Dynamic performance enhancement of DFIG wind turbine using an active disturbance rejection control -based sliding mode control

The present paper proposes a hybrid control law that combines the active disturbance rejection control (ADRC) and the sliding mode control (SMC) to improve the decoupled control of the active and reactive power stator applied to a doubly-fed induction generator (DFIG) integrated into a wind energy conversion system. The stator is directly connected to the electric grid, while the rotor is connected to the electric grid via a back-to-back converter. The Lyapunov theory proves the stability of nonlinear control. The performance of the proposed strategy is compared with that of traditional ADRC and proportional-integral control (PI). The simulation results in MATLAB/SIMULINK environment using a 1.5MW wind system model show the proposed approach. The proposed algorithm shows an excellent dynamic performance that reduces the time response, overshoot, and steady-state error compared to the conventional controllers.Considering parametric variation, applying a novel controller results in fewer oscillations in stator powers, outperforming the PI regulator and classic ADRC.

Backstepping control of DFIG wind turbine system based rotor flux observer

This paper introduces a novel approach to controlling a wind energy system based on a doubly fed induction generator (DFIG) using backstepping control. The proposed control method allows for independent control of the active and reactive power of the stator. Unlike traditional methods that rely on vector control of the stator fluxes and neglect the stator resistance, this approach takes into account the nonlinearities and coupled nature of the system. By using a nonlinear model in the Park frame, the control is more accurate and closer to the behavior of a real machine. This method has yet to consider any estimation of the rotor flux model. Using a high-gain observer can resolve the issue of measuring rotor flux. The stability of the nonlinear observer is demonstrated through the application of Lyapunov theory. The simulation results indicate that the suggested control scheme has enhanced the dynamic performance of the system.

Multiple faults detection in doubly-fed induction generator wind turbine using artificial neural network

The development of fault detection methods in wind turbine (WT), especially for single fault detection, is continuously increasing. However, the rapid growth of fault detection in WT leads to another challenge where multiple faults can occur. The single fault detection method in WT is no longer reliable, especially when multiple faults occur simultaneously. Therefore, multiple faults detection in doubly-fed induction generators (DFIG) WT was proposed using an artificial neural networks (ANN) model. These multiple faults include internal and external stator faults happening simultaneously. Internal stator faults cover inter-turn short circuit faults and open circuit faults, while external stator faults cover loss of excitation and external short circuit faults. The performance of the developed multiple faults detection model was measured using accuracy and the root mean square error (RMSE) value. The results show that the developed model performs well with high accuracy and a low RMSE value. Thus, the developed model can accurately detect the coexistence of multiple faults in DFIG WT.

Experimental Characterization of Common-Mode Voltages and Currents in Gearbox Bearings of a Doubly-Fed Induction Generator Wind Turbine on a Test Bench

Wind turbine (WT) drivetrain failures can lead to expensive repairs and downtime, significantly impacting the Levelized Costs of Electricity (LCOE). Gearbox failures are a major contributor to maintenance costs, with High-Speed-Shaft (HSS) bearings having the highest failure rate. Frequently occurring premature HSS bearing damage indicates design inadequacies. Currently, bearing design standards (DIN/ISO 281) are primarily based on fatigue. Other damage mechanisms like adhesion or damages due to electrical currents passing through the bearings are not considered. WT gearbox bearings are exposed to electrical currents, mainly caused by common-mode (CM) voltages. Bearing currents lead to surface damages and also may promote the formation of white etching areas (WEA) or cracks (WEC) and thus need to be investigated further. The CM voltage is an inherent feature of the power converter, which generates CM currents in the electrical machine. The resulting high voltages at the HSS bearings can lead to electrical discharge currents in the rolling contact, which damage the raceways of the bearing. This paper presents an experimental method for characterization of the currents and voltages that pass from the generator to the HSS of the gearbox in a multi-megawatt WT drivetrain on a test bench. CM currents and voltages measured at the converter are correlated with the shaft voltages at the HSS bearing. The results indicate, that the CM currents directly pass the HSS and its bearings into the gearbox housing. The CM currents show peaks indicating discharge events with over 100 A. Furthermore, at the discharge events, high-frequency oscillations with over 20 MHz are observed in CM current and bearing voltage.

Performance Analysis of Photovoltaic and Wind Turbine Grid-Connected Systems under LVRT Conditions

The integration of grid-connected renewable energy systems has gained significant attention and introduces several challenges and considerations. One of these challenges is ensuring the reliable and stable operation of these systems under various grid conditions. For example, faults at the grid could lead problems such as DC-link over-voltage and AC over-current that may cause disconnection or damage to inverter. This paper presents a comprehensive analysis of the performance of photovoltaic (PV) and doubly-fed induction generator (DFIG) wind turbine grid-connected systems under low voltage ride-through (LVRT) conditions. The study aims to investigate their behavior, and stability during LVRT events and provide insights for enhancing their grid integration capabilities. The PV and DFIG systems are modelled and simulated using MATLAB Simulink under three difference conditions, with and without using reactive current injection and DC chopper circuit. Various performance parameters, including grid voltage, grid current, DC-link voltage, active power, and reactive power, are analyzed to assess the system's behavior and compare their responses. The principal results reveal distinct performance characteristics of the PV and DFIG systems. The PV system shows higher overshoot currents, over-voltage, and significant drops in active power during fault occurrences, while the DFIG system exhibits lower overshoot currents and better stability in the DC-link voltage. Reactive power responses differ between the systems, with the PV system demonstrating a higher capability for support. The implementation of DC chopper shows more effective in the reduction of DC-link voltage and overshoot grid current in the PV system compared to the DFIG system.

Active damping of torsional vibrations in the drive train of a DFIG wind turbine

Torsional vibrations in the drive train of the doubly-fed induction generator (DFIG) based wind turbine can cause large mechanical stress and reduce the life cycle of the components. They can be easily induced by sudden changes from the turbine rotor side or grid side. In this paper, a model-based active damper of the torsional vibration designed with the linear quadratic-Gaussian (LQG) algorithm is proposed. The modelling of the drive train takes the flexibility of the rotor blades into account and utilizes a three-mass model. A combination of different simulation packages, namely FAST (Fatigue, Aerodynamics, Structure, Turbulence) and Matlab/Simulink describing important dynamics of both the mechanical and electrical side, is applied to analyse the vibrations in the drive train and test the algorithm. Simulation results show that the proposed active damping can suppress the torsional vibrations in the drive train effectively even if a gird fault occurs.

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.

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.

Smoothing Intermittent Output Power in Grid-Connected Doubly Fed Induction Generator Wind Turbines with Li-Ion Batteries

Wind energy is an increasingly important renewable resource in today’s global energy landscape. However, it faces challenges due to the unpredictable nature of wind speeds, resulting in intermittent power generation. This intermittency can disrupt power grid stability when integrating doubly fed induction generators (DFIGs). To address this challenge, we propose integrating a Li-ion battery energy storage system (BESS) with the direct current (DC) link of grid-connected DFIGs to mitigate power fluctuations caused by variable wind speed conditions. Our approach entails meticulous battery modeling, sizing, and control methods, all tailored to match the required output power of DFIG wind turbines. To demonstrate how well our Li-ion battery solution works, we have developed a MATLAB/Simulink R2022a version model. This model enables us to compare situations with and without the Li-ion battery in various operating conditions, including steady-state and dynamic transient scenarios. We also designed a buck–boost bidirectional DC-DC converter controlled by a proportional integral controller for battery charging and discharging. The battery actively monitors the DC-link voltage of the DFIG wind turbine and dynamically adjusts its stored energy in response to the voltage level. Thus, DFIG wind turbines consistently generate 1.5 MW of active power, operating with a highly efficient power factor of 1.0, indicating there is no reactive power produced. Our simulation results confirm that Li-ion batteries effectively mitigate power fluctuations in grid-connected DFIG wind turbines. As a result, Li-ion batteries enhance grid power stability and quality by absorbing or releasing power to compensate for variations in wind energy production.

Enhancement of a Grid-Connected DFIG Wind Turbine System Using Fractional Order PI Controllers

The wind velocities are unpredictable, and generating power with persistent speed is difficult which comprises mechanical stress at the rotor that leads to poor efficiency. So, variable wind power speed generation has ample significance with the Doubly Fed Induction Generator (DFIG). For a grid-connected DFIG, the governing of power is done conventionally by employing vector-controlled PI regulators. Yet, the performance of PI regulators depends on system parameters, which motivates the adoption of Fractional Order PI (FOPI) regulators. Presently FOPI regulators are seizing a lot of applications with the assistance of additional tuning parameters. However, tuning FOPI regulators by conventional methods is challenging. So, initially, the Particle Swarm Optimization (PSO) method was used for tuning FOPI regulators, but the disadvantages are low convergence rate, falling into local elucidation, entailing more variables to attune, and requiring a large number of iterations. Thus, this motivates introducing the Ant Lion Optimization (ALO) algorithm in this article due to its better performance and eligibility to overcome the limitations of conventional methods. Furthermore, in the validation of the proposed algorithm, the performance parameters like DC coupling capacitor voltage, rotor Speed, active power, and reactive power with PI, FOPI, PSO-FOPI, and ALO-FOPI regulators are compared and analysed using the bode plot are presented. The time response analysis of all the controllers with PI, FOPI, PSO-FOPI, and ALO-FOPI controllers were also observed with a voltage dip. Finally, the fractional order controllers with frequency response and time response analysis show superior performance in distributed generation with advanced heuristic controllers when compared to conventional controllers. The complete work has been simulated via MATLAB/ Simulation platform.

Comparative Study of Control Methods for a 2MW Doubly-Fed Induction Generator Wind Turbine

This paper presents a comparative study of two control methods for a 2MW Doubly-Fed Induction Generator Wind Turbine (DFIG-WT) using MATLAB Simulink. The Proportional-Integral-Derivative (PID) and Model Predictive Control (MPC) control methods were implemented and evaluated in terms of their ability to track reference signals, disturbances tolerance and stabilize the system under uncertain wind conditions. The performance of the control methods was assessed using a high-fidelity WT model that incorporates the dynamics of the wind turbine, the wind speed, and the control system. The results show that the MPC control method outperform the PID control method in terms of tracking accuracy and disturbance tolerance.

Limits of reactive power compensation of a doubly fed induction generator based wind turbine system

The doubly fed induction generator (DFIG) systems feature a significant amount of free power capacity that may be used for reactive power adjustment when they are put into practical use. This change, which is occasionally overlooked, is a significant one. Using DFIG systems for wind turbines (WT), this paper explored strategies for reducing and using reactive power. In order to investigate the power characteristic and how it is regulated in DFIG systems, a mathematical model for the steady-state performance of DFIG WT has been developed and presented. Here is a detailed derivation of the limiting range of DFIG's reactive power capacity as well as the physical constraints on reactive power output. The distribution of the DFIG WT at a distribution network's end is demonstrated by a simulation example. Within this simulation, reactive power management strategy, load fluctuation, and the change in wind speed are all taken into consideration. Due to the possibility of a rise in the voltage at the access point, can concluded that both acceptable and efficient to use DFIG WT's reactive power capabilities as an additional continuous reactive power source for effectiveness.

Fault tolerant control for DFIG wind turbine controlled by ADRC and optimized by genetic algorithm

This research work deals with the modelling, control and simulation of a wind turbine based on the doubly fed induction generator (DFIG) in the current sensor’s failure event. We present in the first time the model of the wind energy conversion system based on the DFIG and the control by active disturbances rejection control (ADRC) optimized by genetic algorithm. Particular focus is directed towards on a technique for detection, identification, isolation and reconfiguration of current sensor signals after failure. The combination of the two preceding techniques makes it possible to have a fault tolerant control to sensor faults which ensures continuity of service in all circumstances. The robustness of the proposed technique is tested under the MATLAB/Simulink environment.

ANFIS based sliding mode control of a DFIG wind turbine excited by an indirect matrix converter

<span lang="EN-US">Doubly fed induction generator (DFIG) is very popular in commercial turbines installed worldwide. Indirect matrix converter (IMC) is a fully silicon-based converter without capacitor that could be used in wind turbines. In this paper a robust ANFIS based second order sliding mode controller is proposed to control the DFIG wind turbine excited by IMC converter. ANFIS is a combination of fuzzy logic control and artificial neural networks. This hybrid combination could decrease the complexity of the wind turbine system. This scheme does not need the exact mathematical model of the system as needed in classical control methods. The effectiveness of the proposed controller is verified by simulation results compared to the classical PI controller.</span>

Power quality assessment in different wind power plant models considering wind turbine wake effects

Abstract The intense increase in the installed capacity of wind farms has required a computationally efficient dynamic equivalent model of wind farms. Various types of wind-farm modelling aim to identify the accuracy and simulation time in the presence of the power system. In this study, dynamic simulation of equivalent models of a sample wind farm, including single-turbine representation, multiple-turbine representation, quasi-multiple-turbine representation and full-turbine representation models, are performed using a doubly-fed induction generator wind turbine model developed in DIgSILENT software. The developed doubly-fed induction generator model in DIgSILENT is intended to simulate inflow wind turbulence for more accurate performance. The wake effects between wind turbines for the full-turbine representation and multiple-turbine representation models have been considered using the Jensen method. The developed model improves the extraction power of the turbine according to the layout of the wind farm. The accuracy of the mentioned methods is evaluated by calculating the output parameters of the wind farm, including active and reactive powers, voltage and instantaneous flicker intensity. The study was carried out on a sample wind farm, which included 39 wind turbines. The simulation results confirm that the computational loads of the single-turbine representation (STR), the multiple-turbine representation and the quasi-multiple-turbine representation are 1/39, 1/8 and 1/8 times the full-turbine representation model, respectively. On the other hand, the error of active power (voltage) with respect to the full-turbine representation model is 74.59% (1.31%), 43.29% (0.31%) and 7.19% (0.11%) for the STR, the multiple-turbine representation and the quasi-multiple representation, respectively.

Low voltage ride-through augmentation of DFIG wind turbines by simultaneous control of back-to-back converter using partial feedback linearization technique

This paper proposes a nonlinear controller for doubly fed induction generator (DFIG) wind turbines using partial feedback linearization (PFL) technique. The controller generates switching signals for driving both the rotor side converter and grid side converter simultaneously enhancing the low voltage ride through (LVRT) capability over a wide range of operating conditions. The proposed PFL method has been implemented into a partially linearized form of a nonlinear system, where the transformed system has been made autonomous and reduced in order. All calculations in the proposed method except for the control laws have been carried out offline resulting in reduced design and implementation complexity, small computational burden, and offline control tuning with fast tracking performances. The step-by-step approach of control design and implementation includes system modeling and partial linearization, control law derivation, software implementation, and controller tuning. The effectiveness of the proposed controller has been evaluated through electromagnetic transient simulations. The simulations have demonstrated that the controller has successfully augmented the LVRT capability of DFIG wind turbines and has remained robust against diverse wind conditions and voltage sags.

Technical Assessment of the Key LVRT Techniques for Grid-Connected DFIG Wind Turbines

As a key portion of renewable energy resources (RESs), wind energy penetration is rapidly deployed. The effects of grid faults on grid-connected wind turbines (WTs) are causing problems for wind energy producers. To meet the necessary requirements, additional resources and technical interventions are needed. One of these requirements is low voltage ride-through (LVRT) of doubly fed induction generator (DFIG)-based WTs. This means that DFIG-WTs must stay connected to the grid during transient grid faults and supply active and reactive power after the fault is cleared. Many techniques for improving the LVRT capability of DFIG-WTs have been developed and this paper examines them. The paper also evaluates how well they align with grid codes, and offers case studies and simulations of the selected key techniques. Lastly, this paper provides guidelines and suggested designs for the LVRT techniques for DFIG-WTs to ensure they meet local grid codes.

Design of a robust and practicable SSI damping controller using H[formula omitted] technique for series compensated DFIG-based wind farms

This paper designs a robust and practicable subsynchronous interaction (SSI) damping controller using H∞ technique for the safe operation of series capacitor compensated wind farms (WFs) with doubly-fed induction generator (DFIG) wind turbines (WTs). Mixed sensitivity control design together with pole placement are formulated into a set of linear matrix inequalities (LMIs) to obtain the controller parameters. The LMI technique allows to include both desirable frequency and time domain specifications. The proposed damping controller is integrated into the WT controller (WTC) and receives the DFIG converter currents as inputs. The implementation of the proposed controller does not require any communication links between the WTs and WF secondary control layer. The controller output signals are applied to the inner control loops of DFIG converters and are dynamically limited for the desired fault-ride-through (FRT) performance. The effectiveness of the damping controller is verified through detailed electromagnetic transient (EMT) simulations. In these simulations, the complete medium-voltage (MV) collector grid is modeled with all details, and it is assumed that the wind speed at the location of each turbine follows a Gaussian distribution. The collected results confirm the accuracy of the modeling of the entire WF as an aggregated WT with the average wind speed.

Enhancement of LVRT Ability of DFIG Wind Turbine by an Improved Protection Scheme with a Modified Advanced Nonlinear Control Loop

One of the problems with the doubly-fed induction generator (DFIG) is its high vulnerability to network perturbations, notably voltage dips, because of its stator windings being coupled directly to the network. As the DFIG’s stator and rotor are electromagnetically mated, the stator current peak occurs during a voltage dip causing an inrush current to the critical converter back-to-back and an overload of the DC-link capacitor. For this purpose, a series of researchers have achieved a linear and non-linear controller with a crowbar-based protection scheme. With this type of protection, the Rotor Side Converter (RSC) is disconnected momentarily, and consequently, its control of both the active and reactive output power of the stator is totally lost, leading to incorrect power quality at the point of common coupling (PCC). In this document, a robust nonlinear controller by Advanced Backstepping with Integral Action Control (ABIAC) is initially employed to monitor the rotor and the network side converters under normal network operations. In the presence of a network fault, an improved protection scheme (IPS) is tacked on to the robust nonlinear control to help enforce the behavior of the DFIG system to be able to overcome the fault. The IPS, which is formed by a crowbar and an RL series circuit, is typically located in the space between the rotor coils and the RSC converter. Compared to a standard crowbar, the developed scheme is successful to limit the rotor transient current and DC-link voltage, also an RSC disengagement to rotor windings can be prevented during the fault. Furthermore, the controllers of both the RSC and the Network Side Converter (NSC) are modified to boost the supply voltage at the PCC. A comparative study is also performed between the IPS without and with modification of the reactive power control loops. The simulation results mean that with the modified controllers during the fault, the amount of reactive power sustainment with ABIAC at the PCC is optimized to 17.5 MVAr instead of 15 MVAr with proportional-integral control (PIC). Therefore, the voltage at the PCC is fort increased in order to comply with the voltage requirements of the farm and absolutely to maintain the connection to the network in case of voltage dip.

Inclusion of a Supercapacitor Energy Storage System in DFIG and Full-Converter PMSG Wind Turbines for Inertia Emulation

The energy transition towards renewables must be accelerated to achieve climate targets. To do so, renewable power plants, such as wind power plants (WPPs) must replace conventional power plants (CPPs). Transmission System Operators require this replacement to be made without weakening the frequency response of power systems, so it must be ensured that WPPs match the response of CPPs to grid frequency variations. CPPs consist of grid-tied synchronous generators that inherently react to frequency variations by modifying their stored kinetic energy and their output power, thereby contributing to grid stability. Such response is known as inertial response. By contrast, wind turbines (WTs) are mostly based on either doubly-fed induction generators (DFIG) or permanent magnet synchronous generators (PMSG). Their power electronics interface decouples the electromechanical behavior of the generator from the power grid, leading to a negligible inertial response. Therefore, in order to replace CPPs with WPPs, WTs must be able to react to frequency variations by changing their output power, i.e., emulating an inertial response. Currently implemented inertia emulation strategies in WTs rely on pitch control and stored kinetic energy variation. This paper proposes an alternative strategy, using the energy stored in a supercapacitor directly connected to the back-to-back converter DC link to emulate inertia. Its performance is validated by means of simulation for both DFIG and PMSG. Compared to state-of-the-art techniques, it allows a more accurate emulation of grid-tied synchronous generators, favoring the replacement of these generators by WTs.