Induction Generator Wind Turbine Research Articles

Advanced control scheme of doubly fed induction generator for wind turbine using second sliding mode control

This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator(DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC).Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control 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.

A Modified Reduced-Order Generalized Integrator–Frequency-Locked Loop-Based Sensorless Vector Control Scheme Including the Maximum Power Point Tracking Algorithm for Grid-Connected Squirrel-Cage Induction Generator Wind Turbine Systems

A Modified Reduced-Order Generalized Integrator–Frequency-Locked Loop-Based Sensorless Vector Control Scheme Including the Maximum Power Point Tracking Algorithm for Grid-Connected Squirrel-Cage Induction Generator Wind Turbine Systems

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.

Modelling and Simulation of Grid Connected Wind Turbine Induction Generator for Windfarm

As the power generation sector moving towards the sustainability to achieve clean and renewable energy source, the wind power generation plays a vital role due to its abundance in nature. A big chunk of the decrease in carbon emission is a major attribute to the growth of the wind energy sector. Wind turbine production, structural development, logistics, maintenance and R&D are just some of the areas that could benefit from the growth of the wind energy industry. This brought out the attention of researchers of the electrical engineering to focus on wind power generation. It can be more efficient and cost-effective to operate wind turbines as a wind farm rather than individually. This has led to a surge in the construction of wind farms, both onshore and offshore wind farms. Therefore, in this paper, the study and analyse of single Induction generator with wind turbines and 33MW windfarm performance is presented. The simulation result demonstrates the efficiency of DFIG in producing energy at a constant wind speed, as well as its ability to regulate both active and reactive power at steady-state.

Modeling of virtual synchronous controlled-DFIG considering stator voltage control dynamics for transient stability analysis

Transient stability of virtual synchronous controlled (VSynC) equipment is usually analyzed without considering the dynamics of the AC voltage controller. However, neglecting the impact of stator voltage controller dynamics in doubly fed induction generator (DFIG) wind turbine can lead to inaccurate stability assessment results. In this paper, the quantitative analysis of the impact of non-forced magnetic flux and DC voltage fluctuations on transient stability is conducted. Based on these analyses, a simplified DFIG model is proposed, which is approximately equivalent to a synchronous generator with excitation regulator. Then, a discretized step-by-step calculation procedure is introduced for the proposed model. Moreover, the influence of controller parameters on transient stability is analyzed based on the calculation results. Finally, simulations and experimental validations are carried out to demonstrate the effectiveness of the proposed model.

Real-time current sensor fault detection and localization in DFIG wind turbine systems

<span lang="EN-US">The degree of reliability is one of the main issues in having the uninterrupted operation of fault-tolerant measurement and control systems. This paper presents a technique for detecting and localizing current sensor fault in doubly fed induction generator wind turbine systems (DFIG-WT). For this purpose, a methodology divided into three steps has been carried out and is presented as follows: the first step is the application of the zero-sequence component as an indicator of the presence of the sensor fault. The second step is based on the application of Concordia transformation on the current signals to generate different criteria for localizing the faulty sensor. Finally, an artificial neural network model is developed to analyze the localization criteria and identify the faulty sensor. All simulations are carried out in MATLAB/Simulink environment. Results show that the proposed technique is effective and can be used in real-time fault detection and localization in the DFIG-WT.</span>

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.

Control of Cascaded/Brushless Doubly-Fed Induction Motors With Real-Time Torque Optimization

Brushless doubly-fed induction machines offer a potential alternative to regular doubly-fed induction generators for wind turbines, due to higher reliability and lower maintenance costs. As motors and generators, the brushless machines could also be part of new technological solutions for hybrid-electric propulsion, including aircraft propulsion. A main advantage is that most of the power would be transferred from generators to motors without electronic conversion. The paper proposes a new speed control algorithm that maximizes the available torque within the limits of the control winding currents and ensures anti-windup protection. The maximum torque and the control variables are obtained through simple analytical computations. The derivations of the paper are based on a complex-variable representation that simplifies the mathematical model and the control algorithm. Compact formulas specify the controller parameters as functions of the machine parameters and of the desired closed-loop behavior. The results are tested on a laboratory testbed using a cascaded doubly-fed induction motor and demonstrate fast responses reaching torque limits that are computed in real-time by the algorithm. While control is achieved through the converter interfaced with the control windings, the data shows that most of the active and reactive power is exchanged directly through the power windings. Similar results are obtained in simulations of a larger brushless doubly-fed induction motor.

Application of optimal control for wind integrated power system

<div align="center"><span>This paper presents the modeling and application of an optimal controller for frequency and tie-line power stability for a two-area interconnected hydro-thermal power plant having tandem compound non-reheat turbines integrated with wind power generation having doubly fed induction generator (DFIG) wind turbines in each area. The power system is interconnected using AC tie-lines. The designed optimal controller was implemented and the system dynamic responses for three power system model states were obtained considering a 1% load fluctuation in one of the areas. The optimal control strategy presented in this paper depends on formulating an error value and finding the feedback gains corresponding to each state of the system, which are easily attainable as outputs. The analysis was undertaken and verified by calculating the performance index value, the closed ring real and imaginary values, finding the feedback gains, and through graphical simulations of the three system models under investigation. The output of the optimal controller was enhanced when the DFIG-based wind turbines were installed in each area combined with a superconducting magnetic energy storage (SMES) unit and a thyristor control phase shifter (TCPS).</span></div>

Mechanical–electrical‐grid model for the doubly fed induction generator wind turbine system considering oscillation frequency coupling characteristics

AbstractWith the evolution of renewable energies, many doubly fed induction generators (DFIGs) are being connected to the power grid, whose operation and grid‐connection stability have a major impact on the power grid. Currently, most studies focus on either modeling the mechanical–electrical section or the electrical‐grid section, and discussions have been limited to shaft oscillation or frequency coupling problems. In this study, a mechanical–electrical‐grid model of a DFIG was established to examine the impacts of wind speed and system control parameters on electrical damping and grid‐connection stability. The accuracy of the proposed model and validity of the analyses were verified using simulations. The following were observed: (1) In the case of changing wind speeds, the wind speed and the applied control model determine the shaft oscillation of DFIG, whereas the grid‐connected impedance on the rotor side is dependent on the wind speed. (2) At a constant wind speed, changes in control parameters under different control modes affect the dynamic characteristics of the drive train differently, whereas the grid‐connected impedance on the rotor side is primarily determined by the proportional gain of the inner/outer loop of the control system. The conclusions drawn from this study can further improve the safe and stable operation of DFIG wind power generation systems as well as their connection to the power grid.

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.

Output Feedback Stabilization of Doubly Fed Induction Generator Wind Turbines under Event-Triggered Implementations

The robust stabilization of doubly fed induction generators in wind turbines against external disturbances is considered in this study. It is assumed that the angular speeds of wind turbines can only be measured and sent to the controller in a discrete-time fashion over a network. To generate the sampling times, three different triggering schemes were developed: time-triggering, static event-triggering, and dynamic event-triggering mechanisms; moreover, performance comparisons were conducted between such approaches. The design methodology is based on emulation, such that the plant is first stabilized in continuous-time where a robust feedback law is constructed based on the linear quadratic Gaussian regulator (LQG) approach. Then, the impact of the network is taken into account, and an event-triggering mechanism is built so that closed-loop stability is maintained and the Zeno phenomenon is avoided by using temporal regularization. The necessary stability constraints are framed as a linear matrix inequality, and the whole system is modeled as a hybrid dynamical system. A numerical simulation is used to demonstrate the effectiveness of the control strategy. The results show that the event-triggering mechanisms achieve a significant reduction of around 50% in transmissions compared to periodic sampling. Moreover, numerical comparisons with existing approaches show that the proposed approach provides better performance in terms of the stability guarantee and number of transmissions.

A Novel Adaptive Model Predictive Control Strategy for DFIG Wind Turbine With Parameter Variations in Complex Power Systems

In this paper, a novel adaptive model predictive control (MPC) strategy is proposed for doubly fed induction generator (DFIG) wind turbine (WT), which is integrated into a complex power system, in order to improve the power output tracking precision and dynamic performance. Considering the existence of parameter variations in DFIG, an adaptive parameter estimation method is firstly designed. By analysis of stability, the convergence of the parameter estimation algorithm is rigorously proved. Furthermore, the parameter estimation algorithm is effectively integrated into MPC to realize real-time optimal control of DFIG with the adaptive model. To achieve the rotor side converter (RSC) design based on adaptive MPC, the DFIG model is linearized. In addition, a virtual output compensation (VOC) strategy is adopted to alleviate the impact of model linearization errors on the MPC, especially the variation of the model parameter. The newly proposed adaptive MPC-based RSC is capable of greatly improving the tracking performance, meanwhile taking into account the realistic constraints under various operation conditions. The simulation results demonstrate the effectiveness and superiority of the proposed control method.

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.

Modal analysis, control of frequency, and torsional modes of microgrid with doubly fed induction generator wind turbines providing frequency support

AbstractLoad changes in a microgrid comprising diesel generators and wind turbines cause oscillations in system frequency. In this paper, an analytical model that takes wind generator speed deviation into account is proposed to evaluate the oscillation frequency and damping ratio of the frequency mode oscillation when the wind turbines participate in ancillary frequency control. Because the frequency mode oscillation may excite torsional modes, a complete linearized model comprising the diesel generators and the five‐mass drivetrain of the wind turbine is formulated, and the mode shapes as well as the frequencies and damping ratios of the torsional modes are analyzed. To improve damping for the torsional modes, a constant damping ratio design method is proposed to move the eigenvalues of poorly damped modes to points along a line with a constant damping ratio on the complex plane. Dynamic simulations are performed on the microgrid subject to load changes and wind fluctuations in order to validate the results from mode shape analyses as well as demonstrate the effectiveness of the designed torsional damper.

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.

Multiple harmonic sources identification including inverter‐based distributed generations using empirical Fourier decomposition

AbstractThis paper proposes an intelligent approach based on the empirical Fourier decomposition (EFD) to identify harmonic sources at the point of common coupling (PCC) when different inverter‐based distributed generations (DGs) like microturbine (MT), battery energy storage system (BESS), photovoltaic (PV), superconducting magnetic energy storage (SMES), wind turbine with a permanent magnet synchronous generator (PMSG), and doubly‐fed induction generator (DFIG) wind turbine are presented. In order to decrease memory storage and computational burden, strife feature selection is used. Applying just voltage signals consumes less processing time and decreases measurement devices. Moreover, the whale optimization algorithm (WOA) as the optimizer of the parameters of the support vector machine (SVM) classifier is used. Consequently, the results from the proposed method can be helpful for both engineers and researchers to plan and develop a better strategy to mitigate harmonic distortion.

Robust sensor-less sliding mode of second-order control of doubly fed induction generators in variable speed wind turbine systems based on a novel MRAS-ANFIS observer

The current study proposed a robust sensor-less sliding mode second-order based on a super twisting algorithm (STA-SMSO) approach using a new observer Model Reference Adaptive System-Adaptative Neuro-Fuzzy Inference System (MRAS-ANFIS). This model was applied to a doubly fed induction generator (DFIG) wind turbine running under variable wind speed and DFIG fed with a power voltage source without a speed sensor, while the control objective was used to regulate independently, the active and reactive power DFIG stator were decoupled by using the field-oriented control technique. Additionally, this process reduced the cost of the control scheme and the size of DFIG by eliminating the speed sensor (encoder). In order to improve the traditional MRAS, the MRAS-ANFIS observer was proposed to replace the usual PI controller in the adaptation mechanism of MRAS with an Adaptative Neuro-Fuzzy Inference System (ANFIS) controller. The estimation of rotor position was tested and discussed under varying load conditions in low, zero, and high-speed region. The results mentioned that the proposed observer (MRAS-ANFIS) presented an attractive feature, such as guarantees finite time convergence, good response on speed wind variations, high robustness against machine parameter variations, and load variations compared to the conventional MRAS observer and MRAS-Fuzzy. Hence, the estimated rotor speed converged to their actual value has the capacity for estimating position in deferent region (low/zero/high) of speed.