Model Of Doubly Fed Induction Generator Research Articles

Sensorless DFIG System Control via an Electromagnetic Torque Based on MRAS Speed Estimator

The main goals of this research are to develop a method for obtaining the rotor position and speed in a doubly fed induction generator (DFIG) without using sensors in a variable-speed wind turbine installation. The considered method is based on the Model Reference Adaptive System (MRAS). According to this method, electromagnetic torque is used as an error variable for the adaptation process in order to refine the estimate. A good assessment is very important when trying to put into place any strategy that can control the behavior of a DFIG. This method of estimation functions by comparing the actual performance of the DFIG with that of a reference model and adjusting the system parameters to reduce any mismatch between the two. One notable advantage of this developed estimator is its stability across a broad range of speeds. Additionally, it is designed to exhibit resilience in the face of uncertainties in machine parameters. The proportional integral (PI) gains for the MRAS estimator are determined via pole placement. To assess and validate the entire DFIG model and the sensorless estimation method, comprehensive simulations are carried out using MATLAB/Simulink.

Comparison performance study of singly-fed and doubly-fed induction generators-based bond-graph wind turbines model

This paper consecrates to a comparative performance study of singly-fed and doubly-fed of induction generators thrusted by wind power turbine of similar generation capacity of 2.5 kW, and constant or variably wind speed. The singly-fed induction generator model could be represented using natural reference frame and doubly-fed induction generator model is described using a Park reference frame. Because of several physical domains existing in both induction generators like mechanical and electrical, modeling of generators is difficult, therefore the modeling based on physical methods takes a high credibility under these conditions. Among the procedures is Bond-graph method that models the systems based on law of mass conservation and/or law of energy conservation containing in the systems. Modeling the parts of both singly-fed and double-fed induction generators are based on Bond-graph method. We found that the impact of stator coil winding for on the current is in the form of changes of its value and steady state intervals; increasing the number of stator coil windings may also lead to increased stator current and the longer their steady state interval. Our study demonstrates also that doubly-fed induction generator possesses advantages compared to singly-fed induction generator, namely better current quality output and an adaptation to fluctuating wind speeds. The performance study is done in constant and variably wind speeds using simulated results of 20-Sim software.

Blade imbalance fault identification in doubly fed induction generator through current signature analysis using wavelet transform

Using wind turbines (WTs) equipped with doubly fed induction generators (DFIG) is a popular technology for generating renewable energy. To ensure safe operation, prompt maintenance, and better operational reliability, the induction generator used in wind energy must be monitored. In this paper, an analysis is carried out on stator currents of the DFIG machine in a wind farm to identify any blade imbalances in the wind farm. A fault characteristics extraction analysis is carried out on the machine stator currents to detect the fault in the system. Firstly, the mathematical equation of the DFIG blade unbalanced stator current is generated using the DFIG model. Secondly, Park's Transformation is used to modify the stator's 3-phase current. Further, by evaluating the feature frequency amplitude variation in the squared signal by doing a spectral analysis on the stator current vector's squared signal. Lastly, a Simulink model for the DFIG is developed. The suggested approach analyses the fault signal of the imbalanced blade fault at various wind velocities. The outcomes show that the suggested method for diagnosing impeller imbalance faults can successfully locate the fault.

Multi-objective configuration and evaluation of dynamic virtual inertia from DFIG based wind farm for frequency regulation

Modern power systems are gradually evolving into low-inertia systems due to the integration of high penetration of renewable energy and power electronic equipment. For the natural inertia on the rotor, doubly-fed induction generator (DFIG) based wind farms are expected to provide inertia support for systems. The paper proposed an analytical model of DFIG with df/dt inertia control for studying frequency dynamics, and investigates the optimal design of virtual inertia from wind farms, as well as its equivalent inertia contribution to system. The inertia response differences between DFIG and synchronous generator (SG) are discussed and analyzed for the first time, and then to accurately describe the frequency response with low cost, an analytical model of DFIG with inertia control is developed considering wind turbine aerodynamic characteristics. The explicit expression of virtual inertia provided by DFIG is derived according to the kinetic energy equilibrium, and the key factors that dominate the magnitude of virtual inertia are illustrated. Based on the system frequency response model including wind farms, taking the system frequency nadir (SFN) and the time of reaching nadir (ToN) as targets, a multi-objective optimal configuration model of virtual inertia is constructed and solved through MOPSO. The time domain simulations of a generic two machine four bus system and modified IEEE 9-bus test system are both performed in MATLAB/Simulink, the accuracy and efficiency of our proposed DFIG model on system frequency dynamics research are demonstrated, the pareto frontiers of virtual inertia configuration under different working conditions are optimized and analyzed as well as the impacts of different parameters on inertia evaluation.

Magnitude-phase equivalent circuit and steady-state power-angle characteristic analysis of DFIG

Circuit model representing generator characteristics is essential in stability analysis and control system design of doubly-fed induction generator (DFIG). This paper develops the relationship between generated voltage and magnetic field in DFIG, and establishes an equivalent circuit model considering rotor motion. The novel magnitude-phase equivalent circuit (MPEC) model is established based on vector magnitude and angle. Furthermore, the paper analyzes phasor diagrams, calculates the power expression under the MPEC, and obtains steady-state power-angle characteristic of the DFIG. In the proposed power-angle characteristic, the DFIG's output incorporates variations in slip ratio and power-angle, which combines the characteristics of asynchronous and synchronous machines. Based on the proposed MPEC and power-angle characteristic, the steady-state maximum power of the DFIG is determined at the critical stable power-angle of π/2. Finally, simulation and experimental results are given to validate the effectiveness of the proposed equivalent circuit model and power-angle characteristic of DFIG. The results show that the MPEC model is capable of analyzing the DFIG stability from the power-angle motion perspective, and the system exhibits a potential for instability when the power-angle exceeds 1.5.

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.

Analysis and research on short-circuit current characteristics and grid access faults of wind farms with multi-type fans

As the grid-connected capacity of a large number of wind farms continues to increase, their short-circuit current will have a great impact on protection. Therefore, accurate short-circuit current calculation is beneficial for correct protection action evaluation. Considering the issues related to the diversity of wind turbine types in wind farms and the inability to accurately simulate the failure transient process in previous studies, this research focuses on investigating the impact of control strategies during faults on the transient process of wind turbines. In this paper, the single-machine equivalent model of doubly-fed induction generators (DFIG) and permanent magnet synchronous machine (PMSM) is established by considering the types of wind turbines, and the calculation method of short-circuit current of hybrid wind farms is further proposed by using the classification aggregation equivalent effect method. The accuracy of short-circuit current calculation proposed in this article was verified on RTDS, and a power grid fault analysis method suitable for wind farm connection was proposed based on the characteristics of equivalent circuits of DFIG and PMSM during fault steady-state.

The stochastic stability and H∞‐fuzzy control of stochastic bifurcation of a doubly‐fed induction generator

AbstractConsidering the dynamic behavior of doubly‐fed induction generators (DFIGs) under the influence of random factors, this paper not only analyzes the phenomenon of stochastic instability and bifurcation of a DFIG dynamic variable in its random space when they are affected by environmental noise, but also proposes a method based on the Tkagi–Sugneo (T–S) fuzzy control strategy to control its stochastic bifurcation. First, a four‐dimensional stochastic dynamic DFIG model is established by using multiplicative white noise to simulate the influence of environmental noise on electrical variables, and stochastic central manifold theory is used to reduce the dimensionality of a planar model in the bifurcation neighborhood. Then, the stochastic stability of the model is investigated based on singular boundary theory, while the steady‐state probability density of the stochastic DFIG is determined using the Fokker–Plank–Kolmogorov equation to obtain the location and probability density of its stochastic P‐bifurcation. Finally, the influence of stochastic bifurcation behavior is eliminated by H∞‐fuzzy output feedback control. The numerical simulation results indicate that the location and probability of stochastic bifurcation in a DFIG will vary with the change in noise intensity, and the bifurcation parameter values and stochastic stability domain are obtained. The harm caused by random factors can be solved based on H∞‐fuzzy output feedback, which provides a theoretical basis for the stable operation of the DFIG system.

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.

Utilization of superconducting magnetic energy storage and doubly fed induction generator for enhancing stability of interconnected power system

SummaryAs the share of wind power keeps on increasing, the interaction between synchronous and wind generators pose a challenging issue on power system stability. In order to investigate the impact of wind penetration on stability of power system, appropriate modeling of wind energy conversion systems (WECSs) is necessary. Moreover, it is needed to comprehensively study the impact of wind penetration on power system oscillations. This paper presents a didactic approach for integrating a doubly fed induction generator (DFIG)‐based wind farm from SimPower Systems library to a five‐area 68‐bus power system modeled in Simulink. Inter‐area oscillations with and without wind power penetration are investigated for their characteristics. Renewable energy sources are connected to the grid via power electronics converters at the cost of a reduction in inertia. The concept of virtual synchronous generator (VSG) produces virtual inertia by exchanging active power with the power system. The impact of superconducting magnetic energy storage (SMES) and DFIG on enhancing damping performance of inter‐area is investigated. The increase in damping ratios of inter‐area oscillatory modes verifies the enhancement in small signal stability by connecting SMES and DFIG to the power system. The usage of SMES operating in VSG mode to improve the dynamic stability with highly erratic wind profile is also investigated. The developed MATLAB/SIMULINK‐based DFIG model is simple to use and can be expanded to build efficient controllers. The fidelity of the DFIG model and VSG technology is verified in real time by Opal‐RT (OP4510).

Design advantages and analysis of a novel five-phase doubly-fed induction generator

PurposeThe purpose of this paper is to provide an analysis of the performance of a new five-phase doubly fed induction generator (DFIG).Design/methodology/approachThis paper presents the results of a research work related to five-phase DFIG framing, including the development of an analytical model, FEM analysis as well as the results of laboratory tests of the prototype. The proposed behavioral level analytical model is based on the winding function approach. The developed DFIG model was used at the design stage to simulate the generator’s no-load and load state. Then, the results of the FEM analysis were shown and compared with the results of laboratory tests of selected DFIG operating states.FindingsThe paper provides the results of analytical and FEM simulation and measurement tests of the new five-phase dual-feed induction generator. The use of the MATLAB Simscape modeling language allows for easy and quick implementation of the model. Design assumptions and analytical model-based analysis have been verified using FEM analysis and measurements performed on the prototype. The results of the presented research validate the design process as well as show the five-phase winding design advantage over the three-phase solution regarding the control winding power quality.Research limitations/implicationsThe main disadvantage of the winding function approach-based model development is the simplification regarding omitting the tangential airgap flux density component. However, this fault only applies to large airgap machines and is insignificant in induction machines. The results of the DFIG analyses were limited to the basic operating states of the generator, i.e. the no-load state, the inductive and resistive load.Practical implicationsThe novel DFIG with five phase rotor control winding can operate as a regular three-phase machine in an electric power generation system and allows for improved control winding power quality of the proposed electrical energy generation system. This increase in power quality is due to the rotor control windings inverter-based PWM supply voltage, which operates with a wider per-phase supply voltage range than a three-phase system. This phenomenon was quantified using control winding current harmonic analysis.Originality/valueThe paper provides the results of analytical and FEM simulation and measurement tests of the new five-phase dual-feed induction generator.

Adaptive reinforcement learning interval type II fuzzy fractional nonlinear observer and controller for a fuzzy model of a wind turbine

This article presents an innovative control technique for doubly fed induction generator (DFIG) based wind turbine. A DFIG equation is initially presented using fractional order Takagi and Sugeno interval type II fuzzy modeling. Moreover, fault and disturbance are considered in the DFIG model. Then, to design an observer that estimates both fault and disturbance, the fuzzy model of DFIG is decoupled into three subsystems using a different linear coordinate transformation: the state subsystem without disturbance and fault, the subsystem of fault without disturbance, and the subsystem of disturbance without fault. In the following, using the state subsystem, an adaptive reinforcement learning TS interval type II fuzzy fractional sliding mode observer is introduced. The observer gains are adjusted by applying proximal policy optimization, which is a new application of reinforcement learning. Robustness against uncertainties, fast convergence speed of estimation, high degree of freedom and precise estimation are among features of the suggested observer. In addition, only by utilizing the estimated state subsystem and obtained mathematical relationships, the actuator faults and disturbance are estimated. A fractional order sliding mode controller is proposed for the DFIG speed controller. Low chattering characteristics and accurate response are achieved owing to the fractional speed controller. Also, to compensate the influence of disturbances and faults, an adaptive interval type II fuzzy fractional sliding mode controller is used for rotor current regulations, which employs the estimated fault and disturbance. High robustness, fast response time, low tracking error and chattering are some of the advantages of the proposed fault tolerant controller (FTC). The closed-loop stability of controllers is proved by using the Lyapunov theorem. Simulations is accomplished to evaluate the effectiveness of the proposed method. The proposed controller is compared with other controllers. Robustness against parameter uncertainty is also investigated.

Equivalent dimensionality reduction method of doubly‐fed induction generator model and discrimination of Hopf bifurcation type

AbstractThe strong coupling, multivariate, and nonlinear characteristics of the mathematical model of a doubly‐fed induction generator (DFIG) make it challenging to analyze the bifurcation category of the DFIG. Therefore, in this study, we developed a method for analyzing the DFIG model via topologically equivalent dimensionality reduction in the neighborhood of bifurcation values based on the central manifold theorem and realized the discrimination of the Hopf bifurcation type of the DFIG. We established a complex frequency domain model of the DFIG and then calculated the critical open‐loop gain point using the root trajectory method to obtain the relationship between the critical open‐loop gain point and Hopf bifurcation. Thereafter, we performed topological equivalence dimensionality reduction in the neighborhood of the DFIG bifurcation values based on the central manifold theorem. Subsequently, the Hopf bifurcation type of the system was determined using the stability index (first Lyapunov exponent) of the Hopf bifurcation. Finally, a nonlinear time‐domain simulation was used to verify that the four and two‐dimensional DFIGs generate a stable limit cycle by supercritical Hopf bifurcation under the tuning parameter. The results indicated that the proposed method was feasible and effective in the neighborhood of bifurcation values in the state parameter space of DFIG, which provides a theoretical basis for the control of Hopf bifurcation of the DFIG.

Parameter Identification of DFIG Converter Control System Based on WOA

The converter is an important component of a wind turbine, and its control system has a significant impact on the dynamic output characteristics of the wind turbine. For the double-fed induction generator (DFIG) converter, the control parameter identification method is proposed. In this paper, a detailed dynamic model of DFIG with the converter is built, and the trajectory sensitivity method is used to study the observation points that are sensitive to the change of control parameters as the observation quantity for control parameter identification; the Whale Optimization Algorithm (WOA) is used to study the converter control system parameters that dominate the output characteristics of DFIG in the dynamic full-process simulation. To validate the proposed method, four classical test functions are used to verify the effectiveness of the algorithm, and the control parameters are identified by setting a three-phase grounded short-circuit fault under maximum power point tracking (MPPT), and the identification results are compared with particle swarm optimization (PSO) and chaotic particle swarm optimization (CPSO) to show the superiority of the proposed method. The final results show that the proposed WOA can identify the control system parameters faster and more accurately.

Effect of DFIG control parameters on small signal stability in power systems

The doubly-fed induction generator (DFIG) with virtual inertia control and reactive damping control gives a renewable energy generation system inertia and damping characteristics similar to those of a thermal power plant, and the parameters of the control strategy have a direct impact on the small-signal stability of the system. This paper firstly introduces the operating characteristics and control strategies of DFIG-based damping control and virtual inertia control, establishes a small-signal model of the control-based DFIG integrated interconnected system, and investigates the effects of virtual inertia and reactive damping values on the small-signal stability of the system; then, the maximum damping ratio of the interval oscillation mode in small disturbance analysis is taken as the optimization objective, and the control parameters are the optimization variables. An optimization method of inertia and damping parameters is established for improving the small disturbance stability of the system. The results show that the optimization procedure could improve the damping ratio of the interval oscillation mode while ensuring the system frequency. The effects of virtual inertia and reactive damping values on the small signal stability of the system are investigated, and an optimal allocation model and method for virtual inertia used to improve the small disturbance stability of the system is proposed.

Equivalent modeling and multi-parameter coupling optimization for DFIG-based wind farms considering SSO mode

As a low-carbon and environmentally friendly renewable energy source, wind power has been globally recognized as the best solution to achieve energy saving and emission reduction and promote low-carbon economic growth. With the increase of wind power penetration, wind power has a great impact on sub-synchronous state stability and dynamic characteristics of the grid-connected system. Aiming at the fact that the correlation between clustering indexes and sub-synchronous oscillation (SSO) mode and the difference of the contribution to the clustering results are seldom considered in the current equivalent modeling of doubly-fed induction generator (DFIG)-based wind farm, this paper proposes a clustering method based on the index dimension reduction and weighted fuzzy C-means (WFCM) clustering algorithm. Besides, for the SSO study of the grid-connected system without sufficiently considering the coupling effects between controller parameters, a multi-parameter coupling optimization design strategy combining orthogonal experiment method (OEM) and response surface method is proposed. Firstly, the dominant variables of SSO mode of the DFIG-based wind farm connected to weak grid by series compensation system are taken as the initial clustering indexes. After dimension reduction by principal component analysis, the WFCM algorithm is utilized to cluster the wind farm. Then, the proportional and integral coefficients of the grid-side controller, rotor-side controller and phase-locked loop are optimized to achieve the simultaneous optimization of the SSO characteristics and dynamic characteristics of the system. Finally, the interaction between control parameters and the influence degree and trend on the system performance are quantitatively evaluated, and the optimal parameter combination is obtained. The proposed strategy can mitigate SSO more effectively while improving anti-interference than the particle swarm optimization based on OEM.

An impedance matrix model of DFIG for harmonic power flow analysis considering DC-link dynamics

The doubly-fed induction generator (DFIG) has been increasingly used in modern power systems for interfacing wind energies.Because of the nonlinear characteristics of the DFIG, it is important to properly model the DFIG when conducting harmonic analysis in power systems. This is especially important for low-order harmonics that are routinely encountered by present power systems. Therefore, this paper presents a model of DFIG for harmonic power flow analysis. The harmonic model of the back-to-back converters, i.e., the combined rotor-side converter (RSC) and grid-side converter (GSC) unit, is first established through mathematical derivations, and the result shows that it can be represented by a coupled impedance matrix, which includes the harmonic coupling between the RSC and the GSC and coupling between different harmonics. The studies also show that the coupling between different harmonics is negligible; thus, a simplified 2 × 2 impedance matrix can be practically used with confidence. After integrating with the induction generator model, a full harmonic model of DFIG can be obtained through circuit analyses. The correctness of the developed model has been verified using EMT simulations and lab experiments. The new model fills in a gap in the modeling of renewable energies for harmonic power flow analysis.

Complex-Valued Sliding-Mode Control for DFIG Synchronization to Non-Ideal Grids*

Even if the electrical grid is subject to constrained disturbances, doubly-fed induction generator (DFIG)-based wind turbines should be able to synchronize their stator voltage with that of the grid to ensure a smooth connection to the electric power system. In order to face the synchronization task under simultaneously unbalanced and harmonically distorted grid voltages, a complex-valued sliding-mode control (SMC) algorithm, naturally chatter-free and phase-locked loop (PLL)-independent, is proposed. By accomplishing a stationary reference frame-based design, decomposition into positive- and negative-sequences and harmonic components is not required. The finite-time convergence of such algorithm is analytically demonstrated when subject to both parametric and unmodeled uncertainties, as well as disturbances. Simulation over a 2-MW DFIG model has been carried out in order to validate the performance and robustness of the suggested control structure under unbalanced and harmonically distorted grid voltage, variable speed wind profile, substantial parameter deviations and grid frequency variation.

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.