Fed Induction Generator-based Wind Turbine Research Articles

An Improved Strategy of Grid-Forming DFIG Based on Disturbance Rejection Stator Flux Control

Grid-forming (GFM) control are promising for doubly fed induction generator-based wind turbines (DFIG -Based WTs) due to its grid-support ability and stable operation when connected to weak grid. However, GFM-DFIG might suffer from instability under symmetrical grid fault, if its electromagnetic and synchronous dynamics are poor. Therefore, an improved strategy of GFM-DFIG based on disturbance rejection stator flux control (DRSFC) is proposed in this paper. The DRSFC consists of a PI-based rotor-current loop and an active disturbance rejection control (ADRC)-based stator-flux outer loop, and both the better electromagnetic performance and the steady-state voltage source operation are achieved. Besides, impacts of DRSFC on GFM-DFIG are exposed via small-signal and large-signal analysis, and the potential inertia in the inner control loops is revealed. It is suggested that this potential inertia is reshaped by DRSFC, so the impact of inner control loop on the synchronization of GFM-DFIG can be quantitatively studied and controlled. On this basis, a pair of asymmetrical compensation are designed to improve its electromagnetic decay and synchronous dynamic. Finally, experiments are carried out to verify the effectiveness of proposed strategy.

A robust damping control for battery energy storage integrated power systems to mitigate inter-area oscillations

This paper presents the effect of a Battery Energy Storage System (BESS) on the power system inter-area oscillations under changing load conditions. The dynamic interaction between the BESS control modes and synchronous generators, along with BESS control parameters, influence the damping of prominent inter-area oscillations under different loading conditions. Furthermore, H∞ mixed sensitivity scheme-based Wide-Area Damping Controller (WADC) is proposed for BESS. This controller is designed using the Linear Matrix Inequality (LMI) framework to mitigate the prominent inter-area oscillation of the power system. Sensitivity to control parameter variation and the geometric measure of the observability are utilized to select the location and feedback signal for the WADC. The performance of the proposed WADC is compared with an Energy Storage System-based stabilizer and WADC proposed in an existing work on a modified New England ten-machine benchmark system. The Real-Time Digital Simulator (RTDS) platform is used to assess the real-time viability of the proposed WADC. The simulation results demonstrate that the proposed WADC can effectively diminish several inter-area modes. Additionally, it offers robust performance under varying load conditions, contingencies and with communication delays in feedback signals. The proposed controller is also effective under the system integrated with Doubly Fed Induction Generator-based Wind Turbine System.

Protection of Doubly Fed Induction Generator-Based Wind Turbines Against Loss of Excitation of the Rotor Winding

Protection of Doubly Fed Induction Generator-Based Wind Turbines Against Loss of Excitation of the Rotor Winding

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.

Adaptive fractional backstepping intelligent controller for maximum power extraction of a wind turbine system

Controlling wind power plants is a challenging issue, however. This is due to its highly nonlinear dynamics, unknown disturbances, parameter uncertainties, and quick variations in the wind speed profiles. So robust controllers are needed to overcome these challenges. This paper suggests two novel control approaches for doubly fed induction generator-based wind turbines. Its key objective is to regulate the generator speed and rotor currents. A radial basis function (RBF) neural network disturbance observer based fractional order backstepping sliding mode control (SMC) is presented to control the rotor currents. This RBF neural network-based disturbance observer estimates unknown disturbances. Also, a new adaptive fractional order terminal SMC is suggested for the control of the generator speed. This robust chattering-free controller that does not require any information about the bound of uncertainties fractional calculus is adopted in the SMC design to eliminate undesired chattering phenomena. The controller parameters are optimally tuned utilizing the ant colony optimization algorithm. The proposed approach was validated using a simulation study entailing various conditions. Its performance was also compared to that of the conventional backstepping and conventional backstepping sliding mode controller. The simulations results verified the approach's ability to maximize power extraction from the wind and properly regulate the rotor currents. The proposed method has about 20% less tracking error than the other two methods, which means 20% higher efficiency.

Fixed-time fuzzy adaptive control scheme for doubly fed induction generator–based wind turbine

This work focuses on the issue of designing a fixed-time fuzzy adaptive controller for variable-speed doubly fed induction generator-based wind turbine. The main goal is to optimize the wind turbine power production, while improving the performance of the overall control system such as, convergence speed, tracking accuracy, and robustness. For the control design, the backstepping technique is adopted, and fuzzy adaptive systems are employed as universal approximators to estimate continuous functional uncertainties. Using fixed–time stability concept, a detailed mathematical stability proof of the closed-loop control system is performed. Simulation results are presented to testify the efficiency of the designed control approach.

Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization

This work proposes a parallel multi-layer Monte Carlo optimization algorithm (PMMCOA) that optimizes proportional–integral parameters for a doubly fed induction generator-based wind turbine controller. The PMMCOA, an improved form of the Monte Carlo algorithm, realizes the optimization process via a parallel multi-layer structure. The PMMCOA includes rough search layers, precise search layers, and re-precise search layers. Each layer of the PMMCOA adopts a multi-region and multi-granularity approach to increase the diversity and randomness of the search samples. The PMMCOA is employed to tune the controller parameters for achieving maximum power point tracking and improving generation efficiency. The controller fitness function reflects the sum of the rotor angular velocity error and the reactive power error. Compared with the five metaheuristic algorithms, the PMMCOA has a higher global convergence and more accurate power tracking ability.

Integrated Assessment of the Reliability and Frequency Deviation Risks in Power Systems Considering the Frequency Regulation of DFIG-Based Wind Turbines

Recently, frequency regulation strategies have been widely adopted in the operation and control of doubly fed induction generator-based wind turbines (DFIG-WTs). Thus, wind power, which is becoming an increasingly important energy source, is expected to play a significant role in both power generation and frequency regulation in modern power systems. Under such circumstances, maintaining the reliability and frequency of power systems at a designated level may be more challenging due to inherent uncertainties in wind power generation. In this paper, the integrated assessment of the reliability and frequency deviation risks of power systems with a high penetration level of wind power is investigated. A multi-time scale analytical framework is proposed to calculate the integrated reliability and frequency deviation indices. The coupling between the reliability and frequency deviation is further addressed by developing a novel frequency-sensitive reliability model of the electric generator. Frequency deviations under supply/demand fluctuations and device failures are analyzed, and the power system frequency regulation process is modeled with the fuzzy adaptive virtual inertial response of DFIG-WTs and energy storage system (ESS). Furthermore, IEEE-RTS79 is used to verify the validity of the proposed model and solution method.

Analysis of Doubly Fed Induction Generator-based wind turbine system for fault ride through capability investigations

A Doubly Fed Induction Generator has a stator winding directly coupled with grid whereas rotor is to the grid via a fault-prone converter. In early times, when a fault occurred, these generators were required to disengage from the grid. However, due to the increased penetration, grid operators demanded WTs remain connected to the grid. Thus, this paperwork integrates crowbar protection with a Battery Energy Storage System (BESS) to improve Fault Ride Through (FRT) capability. For performance evaluation under transient conditions, a three-phase symmetrical fault is imposed at a time of 2 seconds. By using the suggested technique, the DC-link voltage is observed to improve and remain at 1150 V with minor fluctuation. Likewise, the stator and rotor currents are observed to remain at their nominal value after 2.15 seconds. MATLAB-Simulink software is used for modeling and simulation by obtaining all the system’s actual parameters from ADAMA-II Wind Farm.

Effective PID controller design using a novel hybrid algorithm for high order systems.

This paper discusses the merging of two optimization algorithms, atom search optimization and particle swarm optimization, to create a hybrid algorithm called hybrid atom search particle swarm optimization (h-ASPSO). Atom search optimization is an algorithm inspired by the movement of atoms in nature, which employs interaction forces and neighbor interaction to guide each atom in the population. On the other hand, particle swarm optimization is a swarm intelligence algorithm that uses a population of particles to search for the optimal solution through a social learning process. The proposed algorithm aims to reach exploration-exploitation balance to improve search efficiency. The efficacy of h-ASPSO has been demonstrated in improving the time-domain performance of two high-order real-world engineering problems: the design of a proportional-integral-derivative controller for an automatic voltage regulator and a doubly fed induction generator-based wind turbine systems. The results show that h-ASPSO outperformed the original atom search optimization in terms of convergence speed and quality of solution and can provide more promising results for different high-order engineering systems without significantly increasing the computational cost. The promise of the proposed method is further demonstrated using other available competitive methods that are utilized for the automatic voltage regulator and a doubly fed induction generator-based wind turbine systems.

Probabilistic and Reliability Analysis of an Intelligent Power Control for a Doubly Fed Induction Generator-Based Wind Turbine System

The wind energy system's complicated characteristics have motivated many researchers to develop advanced and intelligent control strategies to ensure reliable and efficient system operation. Over the past few years, Artificial Neural Networks (ANN) have been widely employed in wind energy applications, and they are strongly recommended as a powerful and adequate tool for controlling wind turbine systems.The generator control block is a critical subsystem in the wind turbine chain, where a failed generator power control leads to an unstable operation process. The current work aims to verify the reliability of an ANN control of a DFIG integrated into a wind turbine system by considering the uncertainties in the machine parameters that affect the control's performance requirements. The major challenges encountered when applying reliability analyses are the system's high complexity and the expensive computational time required to achieve accurate results. In this context, the reliability assessment methodology adopted in this study combines Machine Learning techniques and advanced reliability approximation algorithms to optimize the computing time and ensure accurate results despite the system complexity.The obtained results demonstrate the reliability and effectiveness of ANN controllers in coping with machine parameter variations and maintaining the system at its optimal operating point. In addition, the results demonstrate the effectiveness of the reliability methodology implemented in this work by offering accurate approximations with a reasonable computing time.

Extended Simplified Electro-Mechanical Model of a Variable-Speed Wind Turbine for Grid Integration Studies: Emulation and Validation on a Microgrid Lab

The energy transition towards renewable energies is crucial for the sustainable development of a society based on hydrocarbons. The current level of penetration and growth of wind energy in electric power systems is evident and many researchers have presented new methods for simulating and representing the electrical and mechanical characteristics of variable-speed wind turbines. However, complete mathematical models developed and implemented, for example, in MATLAB/Simulink® software, require significant computational efforts that could make grid studies impractical when its scale tends to increase. To contribute to facing this issue, this paper proposes an extended simplified model for a variable-speed wind turbine that considers the dynamic behavior of its mechanical system and includes an approximate representation of the power electronic converter. This approach broadens the scope of studies related to grid frequency control and power quality (fast-frequency response, primary frequency control, and voltage control, among others), considerably reducing the computational burden. Several validations of the proposed simplified model are presented, including comparisons with a doubly fed induction generator-based wind turbine model (phasor type) from the MATLAB/Simulink® library, and laboratory experiments under controlled conditions. The results show a good fit of the proposed simplified model to the MATLAB/Simulink® model, with minimal delays about 3% of the wind turbine inertia constant. Moreover, with the proposal, the computational time is reduced by up to 80% compared to a detailed model. This time reduction is achieved without penalizing the numerical accuracy and the estimation quality of the real behavior of the variable-speed wind turbine.

Artificial Intelligence Control System Applied in Smart Grid Integrated Doubly Fed Induction Generator-Based Wind Turbine: A Review

Wind-driven turbines utilizing the doubly-fed induction generators aligned with the progressed IEC 61400 series standards have engrossed specific consideration as of their benefits, such as adjustable speed, consistent frequency mode of operation, self-governing competencies for voltage and frequency control, active and reactive power controls, and maximum power point tracking approach at the place of shared connection. Such resource combinations into the existing smart grid system cause open-ended problems regarding the security and reliability of power system dynamics, which needs attention. There is a prospect of advancing the art of wind turbine-operated doubly-fed induction generator control systems. This section assesses the smart grid-integrated power system dynamics, characteristics, and causes of instabilities. These instabilities are unclear in the wind and nonlinear load predictions, leading to a provisional load-rejection response. Here, machine learning computations and transfer functions measure physical inertia and control system design’s association with power, voltage, and frequency response. The finding of the review in the paper indicates that artificial intelligence-based machine and deep learning predictive diagnosis fields have gained prominence because of their low cost, less infrastructure, reduced diagnostic time, and high level of accuracy. The machine and deep learning methodologies studied in this paper can be utilized and extended to the smart grid-integrated power context to create a framework for developing practical and accurate diagnostic tools to enhance the power system’s accuracy and stability, software requirements, and deployment strategies.

Coupling DFIG-Based Wind Turbines with the Grid under Voltage Imbalance Conditions

A smooth coupling is implemented between the grid and doubly fed induction generator-based wind turbines (DFIG-WTs) during grid voltage imbalance. The nonlinear characteristics of a grid-connected DFIG-WT system may increase stresses on the mechanical and electrical components of wind turbines. Such difficulties are greatly increased during periods of voltage imbalance. Consequently, in this paper, a new control scheme is proposed to regulate DFIGs in order to support a smooth connection to the grid during voltage imbalance. In synchronization mode, the positive sequence of the rotor dq-axes currents regulates the stator q-axis EMF that is to be synchronized with the q-axis voltage of the grid-side voltage. The phase difference between the grid and stator voltages is compensated by adjusting the stator d-axis EMF to zero. Under normal conditions, a PR controller is used to dampen the negative sequence of the rotor dq-axes currents. PI current controllers are tuned to control the positive sequence of the DFIG rotor currents, while PR current controllers are used to regulate the negative sequence of the rotor currents during synchronization and under normal operation conditions. Experiments are performed to verify the smooth synchronization of the DFIG and the robustness of the proposed control scheme during grid voltage imbalance.

(1912-5600) Type 2 adaptive fuzzy control approach applied to variable speed DFIG based wind turbines with MPPT algorithm

In this research, a Type 2 adaptive fuzzy controller approach is formulated and designed to be applied to variable speed doubly fed induction generator-based wind turbines directly connected to the grid. It brings this study to evaluate the whole operation of the system to capture the highest rate of power in the wind turbines. The controlling approach is considered to keep the stator reactive power to the ideal value. In contrast to the other researches, here the controlling technique is developed through the nonlinear systems. By the aim of making progress in system operation, in contrast with the Type 1 adaptive fuzzy system, type two adaptive fuzzy theory is proposed to approximate a large number of uncertainties and the dynamic nonlinearities, exists in tracking errors which may limit the system performance. Feedback linearization control approach helps us to algebraically alter the system into a linearized plant. Thanks to the Lyapunov theorem, the introduced type two adaptive fuzzy approach is proved to meet the uniformly ultimately boundness (UUB) property. On the other hand, it results better tracking function. The simulation outputs represent that the proposed technique is robust enough in presence of parameter variations and unstructured uncertainties.

Enhancement of new rotor resistance unit for doubly fed induction generator-based wind turbines

It is very important to obtain smooth power and limit over-currents in grid-connected doubly fed induction generator (DFIG)-based wind turbines. Therefore, the rotor resistance unit can be used for power and over-currents control in DFIG. However, it may be insufficient to reduce oscillations in large power systems. This study aims to develop a new rotor resistance unit for low voltage ride through (LVRT) capability in DFIG. Moreover, electromotive-force (emf) models have been also developed in the stator and rotor circuit. The stator emf model of the simulation study was developed in the DFIG for accuracy and speed, while the rotor emf model was developed for over-current occurring in transient situations. In using the new rotor resistance unit and the stator-rotor emf, it was observed that the system stabilized in a short time, and the oscillations formed by the balanced and unbalanced faults on the grid side were damped.

Impact of DFIG-Based WTs on Subsynchronous Oscillation Damping of SG Based on the Net Electrical Damping Method

Subsynchronous oscillations (SSOs) induced during the generation of wind power constitute an important problem that affects the safety and the stability of power systems. It is useful to study the impact of wind turbines on the damping of the SSOs of a synchronous generator (SG). On the one hand, the relevant studies have been based mainly on eigenvalue analysis, which is insufficient, and on the other, an examination of the general mechanism of the SSO is still lacking. Based on the net electrical damping analysis method, this paper examines the dynamic interaction between the SG and doubly fed induction generator-based wind turbines (DFIGs). The self-stabilizing damping coefficient and the mutually stabilizing damping coefficient are proposed from the perspective of the SG, and the effects of different numbers and current loop control parameters of the DFIGs on torsional modes of the SG are analyzed using different grid structures. A time-domain simulation model of DFIGs connected to a power grid is built in EMTDC/PSCAD to verify the correctness of the theoretical analysis.

Crowbar hardware design enhancement for fault ride through capability in doubly fed induction generator-based wind turbines

A crowbar circuit used in doubly fed induction generator (DFIG)-based wind turbines protects the system during transient stability. However, in a large power system, crowbar protection may be insufficient due to over-voltage and inrush currents occurring during balanced and unbalanced faults. Hence, in this study, a crowbar circuit was enhanced for fault ride through capability against balanced and unbalanced faults in a DFIG. The stator and rotor dynamic modeling used a crowbar hardware circuit design with rotor active impedance. Electromotive force voltages were used for the stator–rotor dynamics in the DFIG. Furthermore, crowbar resistance units were designed to meet the fault ride through DFIG requirement. The DFIG behaviors with and without the crowbar hardware circuit design were compared. The balanced and unbalanced faults were also compared in terms of behavior. Results showed that the circuit design of the crowbar hardware enabled the system to promptly become stable and eliminated the oscillations.

Novel active–passive compensator–supercapacitor modeling for low-voltage ride-through capability in DFIG-based wind turbines

Low-voltage ride-through is important for the operation stability of the system in balanced- and unbalanced-grid-fault-connected doubly fed induction generator-based wind turbines. In this study, a new LVRT capability approach was developed using positive–negative sequences and natural and forcing components in DFIG. Besides, supercapacitor modeling is enhanced depending on the voltage–capacity relation. Rotor electro-motor force is developed to improve low-voltage ride-through capability against not only symmetrical but also asymmetrical faults of DFIG. The performances of the DFIG with and without the novel active–passive compensator–supercapacitor were compared. Novel active–passive compensator–supercapacitor modeling in DFIG was carried out in MATLAB/SIMULINK environment. A comparison of the system behaviors was made between three-phase faults, two-phase faults and a phase–ground fault with and without a novel active–passive compensator–supercapacitor modeling. Parameters for the DFIG including terminal voltage, angular speed, electrical torque variations and d–q axis rotor–stator current variations, in addition to a 34.5 kV bus voltage, were investigated. It was found that the system became stable in a short time and oscillations were damped using novel active–passive compensator–supercapacitor modeling and rotor EMF.

Dynamic behavior analysis under a grid fault scenario of a 2 MW double fed induction generator-based wind turbine: comparative study of the reference frame orientation approach

This paper investigates a comprehensive analysis of the dynamic behavior of a typical 2 mw grid-connected double fed induction generator-based wind turbine during a symmetrical grid voltage dip scenario. The stator flux dynamics and the induced rotor electromotive force have been investigated aiming to undertake an accurate assessment of the DFIG behavior. Furthermore, without any complication of the DFIG vector control scheme, the paper offers a comparative study between the use of the stator flux reference frame orientation approach and the grid voltage reference frame orientation approach, this, in order to accurately assess the appropriate choice regarding the stability of the vector control scheme and hence, to have a good background about the LVRT capability of the DFIG during the studied grid fault. The simulation results have been performed through Matlab/Simulink environment.