Doubly Fed Induction Generator Parameters Research Articles

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

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

Proposed sub‐synchronous resonance damping controller for large‐scale wind farms

AbstractThis paper deals with the mitigation of sub‐synchronous resonance (SSR) in doubly‐fed induction generator (DFIG)‐based wind farms using a sub‐synchronous resonance damping controller (SSRDC). The performance of the SSRDC depends on its input control signal and the location of its output control signals. Hence, this paper presents an algorithm to select the best location for applying the SSRDC. The DFIG parameters are used as the inputs of this algorithm. Also, the participation factors analysis is employed as this algorithm's main core. The output of this algorithm determines that the control signal of SSRDC can be applied either in the grid‐side converter (GSC) and/or in the rotor‐side converter (RSC). The best input location in the GSC is the DC‐link voltage and the best input location in the RSC is the q‐component of the rotor voltage. The accuracy of this algorithm was evaluated by investigating the effect of various input signal locations on the SSR using the eigenvalue analysis. This analysis indicated that the dc‐link voltage and the q‐components of the rotor voltage are the most effective signals on the sub‐synchronous oscillatory modes. Moreover, this paper introduces a new SSRDC using these two signals. The performance of this controller is validated through the eigenvalue analysis and a time domain simulation.

Transient stability analysis of DFIG-based wind farm-integrated power system considering gearbox ratio and reactive power control

Nowadays, integration of large-scale wind farms (WFs) into power systems is experiencing rapid growth. As this rapid integration can affect transient stability significantly, employing doubly fed induction generator (DFIG)-based wind turbines, which have shown better behavior regarding system stability, has attracted much attention. This research contributes to the literature by investigating the transient stability of the power system with increasing penetration of DFIG-based WFs. In the proposed framework, the current-balance form is utilized for the network equations, and in this way, transient stability is performed using time-domain simulation. According to the simulation results, when the rate of wind power generation exceeds 0.7 per-unit, the increasing trend of the critical clearing time (CCT) is reversed and the CCT decreases greatly with the increased wind power penetration. In addition, the reactive power compensation by DFIG, the gearbox ratio, the power system strength, and DFIG parameters are comprehensively investigated as effective parameters on transient stability. Since the rated rotor speed of DFIG significantly impacts the electrical torque and machine currents, the reduction of the rated rotor speed due to the change of the gearbox ratio has been investigated as one of the effective factors to improve the transient stability. The simulation results demonstrate the effectiveness of the proposed approach in improving power system transient stability.

Hybrid sliding neural network controller of a direct driven vertical axis wind turbine

This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) scheme for controlling the stator power (active/reactive) of a doubly fed induction generator (DFIG)-based direct drive vertical axis wind turbine (VAWT) power system under a real-world scenario wind speed that will be installed in the Adrar region (Saharan zone) of Algeria. The SM-ANN scheme will control the stator power of the direct drive VAWT power. The chattering phenomenon is the most significant disadvantage associated with sliding mode control (SMC). In order to find a solution to this issue, the artificial neural network (ANN) method was applied to pick the appealing part of the SMC. MATLAB/Simulink is used to do an evaluation, after which the SM-ANN controller being suggested is compared to both traditional sliding mode (SM) and proportional-integral (PI) controllers. The results of the simulation demonstrated that the recommended SM-ANN controller has good performance in terms of enhancing the quality of energy that is delivered to the power network. This is in comparison to the traditional SM and PI controllers, which both have a long history of use. Notwithstanding the fact that there is DFIG parameter fluctuation present.

Control strategy of DFIG and SVG cooperating to regulate grid voltage of wind power integration point

To better solve doubly-fed wind farms' voltage stability control problem with static var generator (SVG), this paper proposes and designs a reactive power regulation strategy based on SVG and doubly-fed wind turbines. To stabilize the voltage of the wind farm, SVG is preferred for reactive power compensation when the voltage fluctuates. After the voltage is stable, the reactive power output of SVG and the doubly-fed induction generator (DFIG) is adjusted according to the system state. The DFIG can output enough reactive power and meet the specified power factor conditions. The control mode adopts a real-time tracking mode to monitor the voltage of the control bus. In the model, comprehensive optimization indexes consider the maximum voltage offset, the time-consuming voltage to enter the stable range, the steady-state voltage deviation, and the average voltage offset in voltage fluctuation. The genetic algorithm optimizes the proportional-integral (PI) controller parameters of DFIG and SVG reactive reference values. DFIG and SVG have better response effects to voltage fluctuation than before optimization. Finally, the grid model of DFIG is built, and the simulation results verify the effectiveness and correctness of the proposed method. The cooperative control strategy of SVG and DFIG can adjust the voltage quickly and avoid the long-term reactive power flow between them.

Sensorless passivity based control of doubly-fed induction generators in variable-speed wind turbine systems based on high gain observer

The current study presents a robust sensorless control using passivity based control (PBC) combined with high gain observer (HGO). The proposed controller is applied to control the generated doubly-fed induction generator (DFIG) active and reactive power installed on a variable speed wind energy conversion system. The control objective is used to regulate independently the DFIG stator active and reactive power, which are decoupled by using the field oriented control technique. Additionally, this process leads to reduce the cost of control scheme by eliminating the speed sensor. Firstly, the DFIG is modeled under the port controlled Hamiltonian (PCH) model, as well as the method of simultaneous injection damping. Then, the DFIG is further modeled by assignment passivity based on the simultaneous injection damping and assignment (SIDA-PBC) control of the obtained model under such conditions and a comparison with the fuzzy sliding mode controller is carried out. Furthermore, the HGO is selected in order to estimate the rotor position and the speed from the measurement of the DFIG currents and voltages, and compared with fuzzy sliding mode observer. For testing the proposed control scheme performance, a 1.5 MW DFIG system is developed and simulated using MATLAB/Simulink. The obtained results demonstrate the effectiveness of the proposed control scheme in the presence of various DFIG parameters variation. Additionally, the control objective is achieved without speed sensor.

Nonlinear Control Strategies for Enhancing the Performance of DFIG-Based WECS under a Real Wind Profile

Wind speed variations affect the performance of the wind energy conversion systems (WECSs) negatively. This paper addressed an advanced law of the backstepping controller (ABC) for enhancing the integration of doubly fed induction generator (DFIG)-based grid-connected WECS under wind range of wind speed. This enhancement was achieved through three control schemes, which were blade pitch control, rotor-side control, and grid-side control. The blade pitch control was presented to adjust the wind turbine speed when the wind speed exceeds its rated value. In addition, the rotor and grid-side converter controllers were presented for improving the direct current link voltage profile and achieving maximum power point tracking (MPPT) under speed variations, respectively. To evaluate the effectiveness of the proposed ABC control, a comparison between PI and sliding-mode control (SMC) was presented, considering the parameters of a 1.5 MW DFIG wind turbine in the Assilah zone in Morocco. Moreover, some changes in the DFIG parameters were introduced to investigate the robustness of the proposed controller under parameter uncertainties. Simulation results showed the capability of the proposed ABC controller to enhance the performance of the DFIG-WECS based on variable speed and variable pitch turbine, at both below and above-rated speed, leading to an error around 10−3 (p.u), with an ATE = 0.4194 in the partial load region; in terms of blade pitch control, an error of 2.10−4 (p.u) was obtained, and the DC-link voltage profile showed a measured performance of 5 V and remarkable THD value reduction compared to other techniques, with a measured THD value of 2.03%, 1.67%, and 1.46% respectively, in hyposynchronous, hypersynchronous, and pitch activation modes of operation. All simulations were performed using MATLAB/SIMULINK based on real wind profiles in order to make an exhaustive analysis with realistic operating conditions and parameters.

Direct Field Orientation Control Based on H∞ Method of Wind Turbine Based on DFIG

This study aims to propose the direct field orientation control based on the H-infinity method (DFOC_ H∞) scheme for controlling the stator power (active/ reactive) of a direct drive vertical axis wind turbine power system based on a doubly fed induction generator (DFIG). the sensitivity to parameters uncertainty of the machine presents the major drawback of the PI controller, in order to cope with this problem; the H-infinity method was used to solve it. The proposed controller H∞ is evaluated with Matlab/Simulink. Simulation results showed that the suggested H∞ controller has a good performance in terms of enhancing the quality of energy provided to the power network. Even in the presence of DFIG parameter variation.

Research on identifying parameter of DFIG-based wind farm based on mathematical mechanization analysis

In order to obtain precise running parameters which are the intrinsic cause resulting in sub-synchronous resonance (SSR) in transmission line with series compensation capacitor, an approach that can be used to identify the dynamic equivalent parameters of DFIG (doubly-fed induction generator) -based wind farm has been proposed based on the mechanized mathematics theory. Core work is to derive the analytical expressions of the stator resistance, inductance and the rotor resistance, inductance and the mutual inductance which are expressed by the sampling voltage, current and active power based on polynomial modelling and characteristic set of the mathematical mechanization. Simulation results which are associates with the actual sampled data of a wind farm show that, the equivalent parameters consist of 32 DFIGs have been given and verified by proposed approach. Also, the maximum identifying error of corresponding resistance and inductance of the stator and rotor was lower than 5% based on sampling an actual DFIG farm. This work can provide a reference for analysing and suppressing SSR which is a bottleneck for a wind farm stable running.

Online Monitoring for Power Cables in DFIG-Based Wind Farms Using High-Frequency Resonance Analysis

Increasing demand for renewable energy has led to a rapid growth of doubly fed induction generator (DFIG)-based wind farms around the world. As a critical component of the DFIG-based wind farms, online monitoring of the connected transmission cable is essential to maintain the reliability of the entire wind power plant. A novel online monitoring method for power cables in DFIG-based wind farms using high-frequency resonance (HFR) analysis is proposed in this paper. The HFR in wind farms due to the interaction between the DFIG unit and the connected cable is firstly modeled and the relationship between the HFR frequency and cable ageing severity is analyzed. An ageing severity estimation algorithm is then proposed based on adaptive hill climbing and particle swarm optimization (AHC&PSO). Simulations for wind farms with both the LCL and L filter are conducted to validate the proposed method. Effective online monitoring and accurate ageing severity estimation of the cables are achieved in the simulations under various operation conditions considering DFIG parameter deviations. Compared with existing approaches, the proposed method provides a superior online monitoring approach to accurately evaluate the ageing state of power cables in wind farms quantitatively with no need of extra monitoring sensors.

A reduced-order model for representing the reactive power response of a doubly fed wind turbine during ZVRT

Zero-voltage ride through (ZVRT) is the worst-case scenario of low-voltage ride through (LVRT), which indicates the optimal fault-response capability of wind turbines (WTs). The reactive response during ZVRT shows the dynamic performance of WTs during extreme grid faults, which greatly improves the flexibility and robustness of renewable-rich grids. The reactive response of a doubly fed (type-3) WT during ZVRT depends on the control strategy of the converter and the steady-state and transient-state performance of the doubly fed induction generator (DFIG). This paper proposes a reduced-order model for representing the reactive response of a type-3 WT during ZVRT including the control strategy of the converter and the equivalent electric circuit of the DFIG, which simplifies some complicated equations but is practical for modeling a renewable-rich power system in most cases. Some simplified expressions between the reactive energy and a single DFIG parameter are presented, which could satisfy the demands of designing a DFIG. Finally, the method of model consistency verification, the influence analysis of DFIG parameters on the reactive response, the reasonable ranges of DFIG parameters and the fault-response performance of the WT in the theoretically longest ZVRT period are also obtained for reference.

A Common Capacitor Based Three Level STATCOM and Design of DFIG Converter for a Zero-Voltage Fault Ride-Through Capability

To meet the augmented load power demand, the doubly-fed induction generator (DFIG) based wind electrical power conversion system (WECS) is a better alternative. Further, to enhance the power flow capability and raise security margin in the power system, the STATCOM type FACTS devices can be adopted as an external reactive power source. In this paper, a three-level STATCOM coordinates the system with its dc terminal voltage is connected to the common back-to-back converters. Hence, a lookup table-based control scheme in the outer control loops is adopted in the Rotor Side Converter (RSC) and the grid side converter (GSC) of DFIG to improve power flow transfer and better dynamic as well as transient stability. Moreover, the DC capacitor bank of the STATCOM and DFIG converters connected to a common dc point. The main objectives of the work are to improve voltage mitigation, operation of DFIG during symmetrical and asymmetrical faults, and limit surge currents. The DFIG parameters like winding currents, torque, rotor speed are examined at 50%, 80% and 100% comparing with earlier works. Further, we studied the DFIG system performance at 30%, 60%, and 80% symmetrical voltage dip. Zero-voltage fault ride through is investigated with proposed technique under symmetrical and asymmetrical LG fault for super-synchronous (1.2 p.u.) speed and sub-synchronous (0.8 p.u.) rotor speed. Finally, the DFIG system performance is studied with different phases to ground faults with and without a three-level STATCOM.

A New Method for Design and Optimization of DFIG for Wind Power Applications

Doubly fed induction generator (DFIG) is one of the important generators that is used in the wind turbines structure. In the previous years, DFIGs based wind turbine system that have installed in the onshore and offshore wind farms have more number than other generators. In this paper, a new method has been presented for design and optimization of a 500 kW DFIG. At first, equations of the optimal design are reviewed for this generator, and then a model is presented for the study of the generator operation. The detailed design of DFIG is done and finite element analysis (FEA) is used to verify the design. In the following, a link is created by a software between FEA tool and genetic algorithm (GA) that is used for optimization. In each iteration, input parameters are changed by GA and is sent to FEA tool for calculation of cost functions. In other words, GA presents a new rotor, and stator slot dimension in each iteration and effect of these parameters is checked on generator operation by FEA tool, e.g., Ansys Maxwell Software. Input parameters that are created the best cost functions are selected as optimized parameters. Rotor and stator slots dimension have been selected as input parameters and cost functions are efficiency, rotor copper loss, and electromagnetic torque. In the results section, a comparison is done between analytical design and FEA design and then output wave of designed DFIG is proposed. In the following, sensitivity analysis is presented that is a study about effect of changing slot dimension on DFIG parameters. Finally optimization results are proposed for each cost function. Results show effectiveness of the proposed method, i.e., we can improve output parameters of DFIG via changing slot dimension.

Improved identification method of doubly-fed induction generator based on trajectory sensitivity analysis

The drive train and generator parameters of doubly-fed induction generator (DFIG) may vary with the operation situation, which is significant for the stability of the DFIG. Previously used identification methods that have more measurements and experience difficulty in operation can easily fall into local optimum, and furthermore, there have been no studies on variable parameters. Therefore, in this study, we propose a novel identification method based on the improved particle swarm optimization (PSO) algorithm and trajectory sensitivity analysis. Initially, the equivalent model of DFIG was established. Selecting active power as a measurement based on trajectory sensitivity analysis can improve the accuracy of the identification method. Thereafter, an improved PSO algorithm compared with genetic algorithm (GA), PSO, and GA-PSO are verified by the classic test functions. Finally, a novel identification method is presented, which only requires one measurement and with no data processing of measurements. This method is suited for both constant and variable parameters. The results of parameter identification demonstrate that the proposed method can improve the accuracy and adaptability of the variable parameters. Besides, the proposed method can be used not only in doubly-fed wind turbines but also in other studies of new energy power generation.

A Novel Adaptive Active Disturbance Rejection Control Strategy to Improve the Stability and Robustness for a Wind Turbine Using a Doubly Fed Induction Generator

A novel and robust active disturbance rejection control (ADRC) strategy for variable speed wind turbine systems using a doubly fed induction generator (DFIG) is presented in this paper. The DFIG is directly connected to the main utility grid by stator, and its rotor is connected through a back-to-back three phase power converter (AC/DC/AC). Due to the acoustic nature of wind and to ensure capturing maximum energy, a control strategy to extract the available maximum power from the wind turbine by using a maximum power point tracking (MPPT) algorithm is presented. Moreover, a pitch actuator system is used to control the blades’ pitch angle of the wind turbine in order to not exceed the wind turbine rated power value in case of strong wind speeds. Furthermore, the rotor-side converter is used to control the active and reactive powers generated by the DFIG. However, the grid-side converter is used to control the currents injected into the utility grid as well as to regulate the DC-link voltage. This paper aims to study and develop two control strategies for wind turbine system control: classical control by proportional integral (PI) and the proposed linear active disturbance rejection control (LADRC). The main purpose here is to compare and evaluate the dynamical performances and sensitivity of these controllers to the DFIG parameter variation. Therefore, a series of simulations were carried out in the MATLAB/Simulink environment, and the obtained results have shown the effectiveness of the proposed strategy in terms of efficiency, rapidity, and robustness to internal and external disturbances.

Equipment-Level Locating of Low Frequency Oscillating Source in Power System With DFIG Integration Based on Dynamic Energy Flow

In view of the complex correlation between Doubly Fed Induction Generator (DFIG) internal components and control links which makes it difficult to locate the oscillating source in the equipment level, a DFIG equipment-level oscillating source locating method based on dynamic energy flow is proposed. Firstly, the energy correlation topology network of DFIG internal components and control links is constructed. On this basis, the analytical expressions of dynamic energy flows of DFIG internal components and control links are derived. And then, through Partial Directional Coherence (PDC) analysis, the values of causality between dynamic energy flows of DFIG internal components and control links are calculated, and the diagram of DFIG internal oscillation transmission causality is depicted. Thus according to the distribution pattern of causality values in the causality diagram, the oscillation transmission route is identified and the oscillating source is located. Finally, simulation tests in Real Time Digital Simulator (RTDS) of IEEE 10-machine 39-bus system verify that, the proposed method can quantitatively describe the intensity of interaction between dynamic energy flows of DFIG internal components and accurately identify the oscillation transmission route and the oscillating source in the equipment level. The proposed method can accurately track the original control link/physical component that causes the system to oscillate. Therefore, this paper will facilitate research on DFIG parameter tuning and oscillation suppression measures for low-frequency oscillation in power system.

Damping Method of High-Frequency Resonance for Stator Current Controlled DFIG System Under Parallel Compensation Grid

High-frequency resonances (HFR) is a subsistent issue in a doubly fed induction generator (DFIG) system when it connects to a parallel compensation grid, due to the insufficient phase margin between the impedance of DFIG and grid. The occurrence mechanism and damping methods for the HFR in the rotor current controlled DFIG have been investigated in the existing literatures, while the appearance and solutions of HFR for the stator current controlled DFIG (SCC-DFIG) have not been studied yet. Based on the impedance of SCC-DFIG, this article analyzes the occurrence mechanism of the HFR in the SCC-DFIG. Thereby, an impedance reshaping method based on stator voltage feedforward controller (SVFC) is proposed. By employing the proposed SVFC, SCC-DFIG can avoid HFR in a wide frequency range, which signifies that HFR with varied resonance frequency caused by the change of compensation degree can be damped well. More importantly, compared to the existing solutions for HFR damping, the impedance reshaping effect of the proposed SVFC for SCC-DFIG is irrelevant to the parameters of DFIG, so that the HFR damping controller can be valid for different DFIG systems without redesigning controller parameters. Theoretical analysis and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Robust Sliding Mode H∞ Controller of DFIG Based on Variable Speed Wind Energy Conversion System

In this study, a Sliding Mode (SM) methodology combined with a robust H∞ control scheme (SM-H∞) was proposed to control the stator active and reactive power generated by the Doubly Fed Induction Generator (DFIG). The purpose of the proposed controller is to improve the DFIG stator active and reactive power tracking performances by reducing chattering phenomena under variable wind speed, which provides major drawbacks of conventional SM controllers. The H∞ technique was used to define the SM attractive control part, which helps to reduce chattering phenomena and improves robustness in the presence of parameter variations and wind speed changing. The DFIG stator was directly connected to the grid and, its rotor was linked to the grid through a back-to-back converter. The proposed approach was tested using Matlab/Simulink and a comparison with the conventional SM and the SM fuzzy logic controllers was carried out. The results of simulation illustrated an effectiveness of the proposed SM-H∞ controller even in the presence of the DFIG parameter variations and speed changing compared with the other techniques.

Stator Harmonic Current Suppression for DFIG System Considering Integer Harmonics and Interharmonics

This paper presents a stator harmonic current suppression method for a doubly fed induction generator (DFIG) under the distorted grid voltage with the consideration of integer harmonics and interharmonics. In the proposed control strategy, the stator current incomplete derivation controller instead of the resonant controller or a repetitive controller is employed to eliminate the negative impacts on the stator current caused by the distorted grid voltage. This approach can provide both the good dynamic response and the strong rejection ability against the integer harmonic voltages with the fixed frequency and the interharmonic voltages with the unfixed frequency. Based on the mathematic model of the DFIG, the stator current incomplete derivation feedback is designed in detail. Then, the robustness against the fundamental frequency variations and the DFIG parameter deviations is analyzed. Finally, the experimental results are presented to validate the effectiveness of the proposed control strategy.

Active and Reactive Power Control of Wind Turbine based on Doubly Fed Induction Generator using Adaptive Sliding Mode Approach

In this work, a robust Adaptive sliding mode controller (ASMC) is proposed to improve the dynamic performance of the Doubly Fed Induction generator (DFIG) based wind system under variable wind speed conditions. Firstly, the dynamic modeling of the main components of the system is performed. Thereafter, the ASMC is designed to control the active and reactive powers of the machine stator. The structure of these controllers was improved by adding two integral terms. Their sliding gains are determined using Lyapunov stability theorem to make them automatically adjusted in order to tackle the external disturbances. Maximum Power Point Tracking (MPPT) strategy was also applied to enhance the power system efficiency. Then, a comparison study with the Field Oriented Control (FOC) based on conventional PI control was conducted to assess the robustness of this technique under the DFIG parameters variations. Finally, a computer simulation was achieved in MATLAB/SIMULINK environment using 2MW wind system model. Satisfactory performances of the proposed strategy were clearly confirmed under variable operating conditions.