Doubly Fed Induction Generator Research Articles

Probabilistic modeling and optimization of microgrids with EV parking lots and dispersed generation

Distributed generation sources provide self-governing power during outages, making microgrids and islanded distribution networks vital for service endurance, superior power quality, reliability, and operative efficiency. However, microgrids structure are difficult to control, particularly in islanded mode where no main power source exists if the main grid fails. Fast responses from discrete generation sources using power electronics can undermine the grid during faults or normal operations without proper regulations. The double-fed induction generator (DFIG) has become the preferred wind turbine generator owing to its low cost and flexibility to varying wind speeds. This paper presents a probabilistic scheduling for day-ahead microgrid programming that includes EV parking lots and dispersed generation resources. The microgrid works in both normal and islanded modes depending on main grid conditions. The uncertainty in EV parking lot usage is modeled hourly using the Z-number method, while wind and solar generation, market prices, and loads are modeled using the Monte Carlo method. Scenario-based incidents in the upstream grid that lead to microgrid islanding are considered, focusing on the time and duration of impact. The optimization model accounts for uncertainty, EV charging/discharging, and operational costs under normal and fault conditions. The fault ride-through (FRT) method for maintaining DFIG stability in islanded microgrids are proposed. In this technique stabilizes terminal voltage during faults by employing a resistor in series with the DFIG stator, enhancing voltage stability and FRT capability. Without these methods, the DFIG may lose stability after clearing transient errors, risking generator loss and threatening microgrid stability, particularly in islanded mode. The effectiveness of these control and protection strategies is validated through comprehensive simulations in MATLAB.

Direct Fractional-Order Adaptive Control Design for Cascaded Doubly-Fed Induction Generator (CDFIG) in a Wind Energy System

This paper is devoted to a fractional-order model reference adaptive control (FO-MRAC) synthesis for the independent control of the active and reactive power flows in the cascaded doubly fed induction generator (CDFIG) in wind energy systems. The proposed adaptive control law combines a second-order-like fractional reference model and a direct MIT adaptation law using a fractional order integrator. This generator configuration can be an interesting alternative to standard double-output wound rotor induction generators. It is made up of two identical wound rotor induction motors such that their rotors are mechanically and electrically coupled. Using two cascaded induction machines permits the elimination of the brushes and copper rings in the traditional doubly-fed induction generator DFIG, which makes the system more resistant and reduces maintenance costs. In the first step, we propose a classical PI controller synthesis to regulate the active and reactive power produced by CDFIG. Then, the FO-MRAC design is realized and a comparative study based on numerical simulations is performed between the classical regulators PI, MRAC, and FO- MRAC, to demonstrate the superiority of the proposed fractional-order adaptive controller relative to conventional integer order PI and MRAC controllers. These results illustrate the reliability and efficiency of the proposed adaptive control scheme.

A frequency control strategy with DC microgrid systems for EV stations

ABSTRACT Fluctuations in power supply and demand lead to frequency deviations, which have detrimental effects on the operation of electrical devices and equipment. Therefore, the implementation of effective frequency control mechanisms is essential for enhancing the strength and dependability of microgrid systems. Research aims to develop a frequency control mechanism for an electrical grid system that integrates both wind and photovoltaic (PV) energy sources. The proposed system utilises a Doubly Fed Induction Generator (DFIG) system with frequency controller for regulating frequency and balancing source and demand of power in the grid. To optimise the solar power output, a Luo converter is implemented, which offers high efficiency with improved conversion of power. Additionally, an adaptive neuro fuzzy inference system (ANFIS) maximum power point tracking (MPPT) controller is engaged to ensure optimal regulation of photovoltaic system. DC link obtained from the PV system is then utilised for powering DC loads and charging electric vehicles (EVs) effectively. In order to accomplish this, a bidirectional converter is used, which permits power flow in both ways and facilitates effective EV charging from the microgrid system. The validation of research is conducted on MATLAB software, and the results proves greater converter efficiency of 94.93%, with reduced total harmonic distortion (THD) of 1.24%.

Double-pancake superconducting coil integrated with DFIG-based wind power systems under voltage-dip events: Design and performance analysis study

The doubly fed induction generator (DFIG)-based wind turbine provides massive development in power generation. Uncertain power oscillations and voltage-dip events affect the stability of the DFIG. To mitigate the effect of voltage-dips in short period, superconducting magnetic energy storage (SMES), which possess rapid energy exchange and high power density, is integrated with large-scale renewable power systems. SMES is integrated at the DC link of the DFIG to ensure the power balance and fault ride-through (FRT) capability. During this operation, frequent current changes occur in the high-temperature superconducting (HTS) coil, which leads to an increase in AC losses. As a remedy, an additional power converter structure controlled with a model-predictive controller (MPC) is proposed. Firstly, a scale-down HTS double-pancake coil model is designed using a finite element model by which transport current loss and magnetic field formulation are studied. Additionally, the critical coil current is also verified through experimental studies. The effectiveness of the proposed MPC-based SMES integrated DFIG on DC link voltage and grid current under IEC-61000-4-11 standard, symmetrical and asymmetrical voltage-dip cases are investigated. The obtained results demonstrate that the proposed system effectively reduces transients in DC link voltage and improves the FRT capabilities of the grid.

A high robust control scheme of grid‐side converter for DFIG system

AbstractIn this study, a high robust control—second‐order sliding‐mode control (SOSMC) scheme is proposed to improve the DC‐link voltage dynamic performance of the grid‐side converter (GSC) for the doubly‐fed induction generator (DFIG) system under the wind turbine power disturbance and DC‐link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC‐link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC‐link voltage controller of the GSC for the DFIG system in this study. By using the non‐linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC‐link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform.

Review of Low Voltage Ride-Through Capabilities in Wind Energy Conversion System

The significance of low voltage ride-through (LVRT) capability in wind energy conversion systems (WECSs) is paramount for ensuring grid stability and reliability during voltage dips. This systematic review delves into the advancements, challenges, and methodologies associated with LVRT capabilities in WECSs. By synthesizing recent research findings, this review highlights technological innovations, control strategies, and regulatory requirements that influence LVRT performance. Key insights include the efficacy of various LVRT techniques, the role of grid codes in shaping LVRT standards, and the integration of advanced control algorithms to improve system resilience. The study offers a comprehensive understanding of the current landscape of LVRT in WECSs and pinpoints future research directions to optimize their performance in increasingly complex grid environments. During the LVRT process, the stator of a double-fed induction generator (DFIG) is directly linked to the power grid. When the external power grid experiences a failure, the stator flux produces a significant transient component, resulting in substantial overvoltage and overcurrent on the rotor side of the DFIG. Failure to implement preventative measures may result in damage to the converter, therefore compromising the safety and stability of how the power system functions.

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

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

Nonlinear integral backstepping control based on particle swarm optimization for a grid-connected variable wind energy conversion system during voltage dips

Double-fed induction generator (DFIG) wind turbines connected to the grid are particularly subject to grid problems such as voltage dips. Because of this, it might be challenging to maintain system stability and prevent system disconnections when using a Proportional-Integral (PI) Controller to operate this system. This paper applies the Integral Backstepping Control for the wind power plant system connected to the power grid. The Integral Backstepping is a nonlinear and recursive method that employs the Lyapunov theory to ensure the system's stability. The best selection of gain values for the Lyapunov function guarantees improved system control. These gains are frequently adjusted using the trial-and-error strategy, which is time-consuming and inefficient. This technique becomes more complex when many parameters need to be determined. It also limits the system's performance and restricts this nonlinear approach's advantages. The objective is to apply the particle swarm optimization for computing several constant values of the nonlinear approach by minimizing an integral absolute error criterion index. The weighted sum of errors is employed to solve the multiple objective problems. The proposed controller tracks the maximum power point, maintains the voltage of the DC-Link constant, and controls active and reactive power. The robustness of this method is verified in critical conditions, including system parameter variation and asymmetrical and symmetrical grid faults. The simulation findings highlight the effectiveness and robustness of the combination of Integral Backstepping with Particle Swarm Optimization in terms of reducing response time from 10.6 (ms) to 2 (ms), canceling static error, and improving overshoot compared to the vector control based on PI regulator. Besides, the DC-Link voltage ripples during the asymmetrical grid faults are reduced to ±1 (V) using the suggested controller. The latter can be implemented thanks to advancements in Central Processor Unit technology.

Protection of rotor side converter of doubly fed induction generator based wind energy conversion system under symmetrical grid voltage fluctuations

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made.

Identification of Sub-Synchronous Oscillation Mode Based on HO-VMD and SVD-Regularized TLS-Prony Methods

To reduce errors in sub-synchronous oscillation (SSO) modal identification and improve the accuracy and noise resistance of the traditional Prony algorithm, this paper focuses on SSOs caused by the integration of doubly fed induction generators (DFIGs) with series compensation into the grid. A novel SSO modal identification method based on the hippopotamus optimization–variational mode decomposition (HO-VMD) and singular value decomposition–regularized total least squares–Prony (SVD-RTLS-Prony) algorithms is proposed. First, the energy ratio function is used for real-time monitoring of the system to identify oscillation signals. Then, to address the limitations of the VMD algorithm, the HO algorithm’s excellent optimization capabilities were utilized to improve the VMD algorithm, leading to preliminary denoising. Finally, the SVD-RTLS-improved Prony algorithm was employed to further suppress noise interference and extract oscillation characteristics, allowing for the accurate identification of SSO modes. The performance of the proposed method was evaluated using theoretical and practical models on the Matlab and PSCAD simulation platforms. The results indicate that the algorithms effectively perform denoising and accurately identify the characteristics of SSO signals, confirming its effectiveness, accuracy, superiority, and robustness against interference.

Comparative study of improved control strategies for DFIG in wind energy conversion systems: A dSpace real-time implementation approach

This research paper focuses on the comparison of two distinct strategies for direct power control (DPC) of a doubly fed induction generator (DFIG) in wind energy conversion systems (WECSs). The study places particular emphasis on algorithms based on low-pass filters for the estimation of stator and rotor flux, which have demonstrated good performance characteristics. Detailed theoretical analysis and implementation procedures of the proposed methods are presented. To evaluate and compare the performance of the control strategies, MATLAB/Simulink software is utilized for comprehensive analysis. The obtained results, both quantitative and qualitative, from this comparative analysis are expected to be of great interest to researchers engaged in the field of DFIG-based WECSs. Furthermore, real-time validation is conducted to demonstrate the effectiveness of the proposed control strategy, specifically focusing on the DPC approach based on stator flux estimation. A dSpace 1104 real-time card is employed and tested with a wind turbine emulator. The experimental results obtained through this validation process provide evidence of the efficiency and validity of the proposed control strategy. Overall, this research contributes to the advancement of DPC strategies for DFIG-based WECS by comparing and evaluating different control methods, providing in-depth theoretical analysis, and validating the proposed approach through real-time experimentation. The findings affirm the efficiency and effectiveness of the proposed control strategy, further establishing its value in practical applications.

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.

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Analysis of Influence of Grid-Following and Grid-Forming Static Var Generators on High-Frequency Resonance in Doubly Fed Induction Generator-Based Wind Farms

In Doubly Fed Induction Generator (DFIG)-based wind farms with Static Var Generators (SVGs), high-frequency resonance will be more like to occur when an unloaded cable is put into operation, which will threaten the stable operation of the wind farm. To address this issue, the influence of power outer loops on the impedance of grid-connected inverters is considered. Based on harmonic linearization, theoretical models for the sequence impedances of DFIGs, Grid-following (GFL) SVGs, and Grid-forming (GFM) SVGs are established. The correctness of the three models is verified by impedance scanning using the frequency sweep method. Through a comparative analysis of these sequence impedances, it is found that unlike the GFM SVG (which exhibits inductive impedance), the GFL SVG exhibits capacitive impedance in the high-frequency band, which leads to negative damping characteristics in the high-frequency band for the wind farm system with the grid-following SVG; thereby, the risk of high-frequency resonance also increases accordingly. On the contrary, GFM control adopted by SVGs can effectively eliminate the negative damping region in the high-frequency band for wind farms to suppress high-frequency resonance. Meanwhile, for grid-forming SVGs, the parameter variations in power synchronous loops have no significant impact on the suppressing effect of high-frequency resonance for wind farms. Finally, an electromagnetic simulation model for a DFIG-based wind farm system with an SVG is established using the StarSim-HIL (hardware-in-the-loop) experiment platform, and the simulation results validate the correctness of the theoretical analysis.

A two-stage subsynchronous oscillation assessment method for DFIG-based wind farm grid-connected system

In the power system, the wind farm based on Doubly-Fed Induction Generator (DFIG) may lead to Subsynchronous Oscillation (SSO), which poses a challenge to the stability of the power grid. In order to accurately evaluate SSO, this paper proposes a new evaluation method. It is divided into two main stages: firstly, the interference level of Phasor Measurement Unit (PMU) data is identified by using the classification model based on Upper Confidence Bound (UCB) and Double Deep Q Network (DDQN). Then, an SSO parameter estimation model based on Local Feature Fusion Transformer (LFF-Transformer) network is designed for data with different interference levels. Experimental results show that the errors of eRMSE-f and EMAPE-F are 0.001 and 0.003 respectively, and the errors of eRMSE-δ and EMAPE-δ are 0.009 and 0.015 respectively. In terms of training and testing time, this method is 90 s and 18 s respectively, which is significantly better than Multi-SVR and Multi-CNN. After application, the frequency deviation decreased from 0.05 to 0.02 Hz, the voltage deviation decreased from 3.5 to 1.5%, the power fluctuation decreased from 10 to 5 MW, the SSO frequency decreased from 1.5 Hz to less than 0.5 Hz, and the SSO damping ratio increased from 0.08 to 0.15. This shows that the proposed method effectively increases the stability of the power grid.

Impact of Phase Angle Jump on a Doubly Fed Induction Generator under Low-Voltage Ride-Through Based on Transfer Function Decomposition

During the fault period, a phase angle jump may occur at the stator or the point of common coupling, which will deteriorate the low-voltage ride-through (LVRT) characteristics of a doubly fed induction generator (DFIG). The existing LVRT studies focus on the impact of a voltage drop on DFIGs but often ignore that of a phase angle jump. The time-domain simulation is accurate in describing the response of a DFIG during the LVRT process, but it is time-consuming for a DFIG with the full-order model. In this paper, by using the voltage magnitude and phase angle of the stator or the point of common coupling as the inputs, and the state variables as the outputs, the transfer function of a DFIG is derived to analyze its response and find the LVRT measures against the voltage drop and, especially, the phase angle jump. Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. Finally, the simulation results of the DFIG are provided to verify the accuracy of the transfer function model and its reduced-order form and validate the feasibility of the LVRT against the phase angle jump with the proposed models.

Optimal control of a doubly fed induction generator of a wind turbine in cooperation with weak and rigid grids

In this article a control method for a rotor side converter (RSC) of a doubly fed induction generator of a wind turbine is developed. The doubly-fed induction generator (DFIG) system of a wind energy power plant that improves grid symmetrization was applied. The issue of optimal control was treated as an extended linear quadratic regulator (ELQR) having an extra set of exogenous inputs, which are source voltages of the electric grid. No additional knowledge of equations modelling the exogenous inputs was assumed. The proposed method is much more efficient than the currently available linear quadratic control methods. The control objective for a weak grid was to maintain the given value of the voltage module on load terminals and the given value of active power transferred from the stator’s winding. First harmonic components of relevant waveforms were used for this purpose. This task also required the DFIG system to provide reactive power to the grid. In the case of a rigid grid, this reactive power would be too high. Therefore, in this case, it was assumed that the system would supply only part of the required active and reactive power, based on its capabilities. It was required that the voltage and current ratings of the system, mainly the DFIG, were not exceeded. Therefore, the parameters of the network in these difficult failure cases were corrected only partially. The behaviour of the grid in the conditions of failure, as well as the return to the steady state after failure disappearance, were studied.

Backstepping control of multilevel modified SVM inverter in variable speed DFIG-based dual-rotor wind power system

The backstepping control (BC) scheme has been successfully used in a variety of high-effectiveness industrial AC drives. This study presents the application of the BC technique based on multilevel modified space vector modulation (BC-MSVM) to get better the energy performance of a dual-rotor wind turbine system (DRWT). Two techniques are suggested to command the stator power of a doubly-fed induction generator (DFIG) driven by a DRWT. This work addresses the problems of the DRWT-based energy production system, such as stream fineness, power overshoot, and torque ripples. The use of a multilevel inverter in BC-MSVM led to an enhancement in the competence of the multilevel BC-MSVM technique and the system as a whole, and this is proven by the results performed using MATLAB software on a 1500 kW DFIG-DRWT. The use of a seven-level inverter led to a minimization in the rates of overshoot, ripples, steady-state error, and response time of active power by 26.66%, 53.84%, 2.09%, and 9.09%, respectively. Regarding the reactive power, the ratios were estimated at 18.12%, 34%, 25%, and 1.41%, respectively. These ratios prove that using a higher-level inverter significantly improves the voltage quality and characteristics of the DFIG-DRWT.

Enhancing pitch angle control in variable speed doubly fed induction generator based wind energy conversion system using advanced adaptive neuro-fuzzy approach with particle swarm optimization

Pitch angle control is a common method used to smooth out output power fluctuations in the wind turbines. This paper focuses on Particle Swarm Optimization (PSO) based Adaptive Neuro-Fuzzy Inference System (ANFIS) pitch angle control scheme for a variable speed Doubly Fed Induction Generator (DFIG) based wind energy conversion system designed for operation in high wind speed regions. The proposed enhanced adaptive controller comprises both Sugeno type fuzzy inference system (FIS) and neural network architecture. In the Sugeno type FIS, the membership functions are optimized using a revisited PSO method. The primary objective is to control the pitch angle to ensure that generator power and speed operate within desired references, reducing fluctuations and minimizing mechanical blade stress. A MATLAB/SIMULINK model of wind energy conversion system setup is prepared and simulations are conducted using different control methods. The effectiveness of the proposed approach is confirmed based on the simulation results.

Tracking performance and power quality enhancement of DFIG based wind turbine using robust integral terminal sliding mode control

The aim of this work is to develop a robust Integral Terminal Sliding Mode Control (ITSMC) strategy for a Doubly Fed Induction Generator (DFIG) wind turbine (WT) operating in challenging conditions. This controller is designed to manage the system's rotor side converter (RSC) and grid side converter (GSC), ensuring maximum power production, improved power quality, and accurate tracking of system state variables, even in the face of fluctuating wind conditions, parameter uncertainties, and external disturbances. The stability of the proposed controller is assured using the Lyapunov theory. The performance of ITSMC is compared with that of the conventional sliding mode controller (SMC) and backstepping controller through simulation tests, using the integral absolute error (IAE) as a performance metric. The results highlight the superiority of ITSMC, demonstrating its ability to precisely track reference values, eliminate static errors, and minimize chattering. ITSMC consistently achieves the lowest IAE for all tracked state variables and across all test scenarios. A comparative study analyzing the Total Harmonic Distortion (THD) of the proposed controller versus SMC, the backstepping controller, and other similar works in the literature shows a marked improvement in the THD of stator and filter currents by at least 24.53 % and 7.96 %, respectively. These findings underscore the controller's capability to enhance the power quality delivered to the grid.