Search Results (331)

This work proposes an effective control technique for enhancing the stability of Doubly Fed Induction Generator-Based Wind Turbines (DFIG-WTs) connected to the grid during voltage sag and swell events, ensuring the reliable and efficient operation of wind energy systems integrated with the grid. The proposed approach integrates a Dynamic Voltage Restorer (DVR) in series with a Wind Turbine Generator (WTG) output terminal to enhance the Fault Ride-Through (FRT) capability during grid disturbances. To develop a flexible control strategy for both unbalanced and balanced fault conditions, a combination of feedforward and feedback control based on a sliding mode control (SMC) for DVR converters is used. This hybrid strategy allows for precise voltage regulation, enabling the series compensator to inject the required voltage into the grid, thereby ensuring constant generator terminal voltages even during faults. The SMC enhances the system’s robustness by providing fast, reliable regulation of the injected voltage, effectively mitigating the impact of grid disturbances. To further enhance system performance, Model Predictive Control (MPC) is implemented for the Rotor-Side Converter (RSC) within the back-to-back converter (BTBC) configuration. The main advantages of the predictive control method include eliminating the need for linear controllers, coordinate transformations, or modulators for the converter. Additionally, it ensures the stable operation of the generator even under severe operating conditions, enhancing system robustness and dynamic response. To validate the proposed control strategy, a comprehensive simulation is conducted using a 2 MW DFIG-WT connected to a 120 kV grid. The simulation results demonstrate that the proposed control approach successfully limits overcurrent in the RSC, maintains electromagnetic torque and DC-link voltage within their rated values, and dynamically regulates reactive power to mitigate voltage sags and swells. This allows the WTG to continue operating at its nominal capacity, fully complying with the strict requirements of modern grid codes and ensuring reliable grid integration. Full article

Split-shaft wind turbines decouple the turbine’s shaft from the generator’s shaft, enabling several modifications in the drivetrain. One of the significant achievements of a split-shaft drivetrain is the reduction in size of the excitation circuit. The grid-side converter is eliminated, and the rotor-side converter can safely reduce its size to a fraction of a full-size excitation. Therefore, this low-power-rated converter operates at low voltage and handles regular operations well. However, fault conditions may expose weaknesses in the converter and push it to its limits. This paper investigates the effects of the reduced-size rotor-side converter on the voltage ride-through capabilities required from all wind turbines. Four different protection circuits, including the active crowbar, active crowbar along a resistor–inductor circuit (C-RL), series dynamic resistor (SDR), and new-bridge fault current limiter (NBFCL), are employed, and their effects are investigated and compared. Wind turbine controllers are also utilized to reduce the impact of faults on the power electronic converters. One effective method is to store excess energy in the generator’s rotor. The proposed low-voltage ride-through strategies are simulated in MATLAB Simulink (2022b) to validate the results and demonstrate their effectiveness and functionality. Full article

Aiming at the transient overcurrent problem faced by doubly-fed induction generators (DFIGs) during continuous voltage fault ride-through, a segmented control strategy based on the rotor side converter (RSC) is proposed. First, through theoretical analysis of the relationship between stator current and transient induced electromotive force (EMF) in each stage of continuous faults, a feedforward control strategy based on the transient component of stator current is proposed. The observable stator current is extracted for its transient component, which is used as a rotor voltage compensation term to effectively counteract the influence of transient EMF. Meanwhile, a fuzzy control algorithm is introduced during the low voltage ride-through (LVRT) stage to dynamically adjust the virtual resistance value, enhancing the system’s damping characteristics. Studies show that this strategy significantly suppresses rotor current spikes in all stages of voltage ride-through. Finally, simulation results verify that the proposed method improves the ride-through performance of DFIG under continuous voltage faults. Full article

Doubly Fed Induction Generator (DFIG)-based Wind Energy Systems (WESs) have become increasingly prominent in the global energy sector, owing to their superior efficiency and operational flexibility. Nevertheless, DFIGs are notably vulnerable to fluctuations in the grid, which can result in power quality issues—including voltage swells, sags, harmonic distortion, and flicker—while also posing difficulties in complying with Fault Ride-Through (FRT) standards established by grid regulations. To address the previously mentioned challenges, this paper develops an integrated approach utilizing a Dynamic Voltage Restorer (DVR) in conjunction with a Lithium-ion storage system. The DVR is coupled in series with the WES terminal, while the storage system is coupled in parallel with the DC link of the DFIG through a DC/DC converter, enabling rapid voltage compensation and bidirectional energy exchange. Simulation results for a 2 MW WES employing DFIG modeled in MATLAB/Simulink demonstrate the efficacy of the proposed system. The approach maintains terminal voltage stability, reduces Total Harmonic Distortion (THD) to below 0.73% during voltage sags and below 0.42% during swells, and limits DC-link voltage oscillations within permissible limits. The system also successfully mitigates voltage flicker (THD reduced to 0.41%) and harmonics (THD reduced to 0.4%), ensuring compliance with IEEE Standard 519. These results highlight the proposed system’s ability to enhance both PQ and FRT capabilities, ensuring uninterrupted wind power generation under various grid disturbances. Full article

This research introduces an enhanced fault detection approach, variational mode decomposition (VMD), for identifying open-circuit IGBT faults in the grid-side converter (GSC) of a doubly fed induction generator (DFIG) wind turbine system. VMD has many advantages over other decomposition methods, notably for non-stationary signals and noise. VMD’s robustness stems from its ability to decompose a signal into intrinsic mode functions (IMFs) with well-defined centre frequencies and bandwidths. The proposed methodology integrates VMD with a hybrid convolutional neural network–long short-term memory (CNN-LSTM) architecture to efficiently extract and learn distinctive temporal and spectral properties from three-phase current sources. Ten operational scenarios with a wind speed range of 5–16 m/s were simulated using a comprehensive MATLAB/Simulink version R2022b model, including one healthy condition and nine unique IGBT failure conditions. The obtained current signals were decomposed via VMD to extract essential frequency components, which were normalised and utilised as input sequences for deep learning models. A comparative comparison of CNN-LSTM and CNN-only classifiers revealed that the CNN-LSTM model attained the greatest classification accuracy of 88.00%, exhibiting enhanced precision and resilience in noisy and dynamic environments. These findings emphasise the efficiency of integrating advanced signal decomposition with deep sequential learning for real-time, high-precision fault identification in wind turbine power electronic converters. Full article

Amid the global transition toward sustainable energy, regional power grids with high wind power penetration are increasingly emerging. The implementation of frequency control is critically essential for enhancing the frequency support capability of grid-connected devices. However, existing studies indicate this may induce ULFOs (ultra-low frequency oscillations). Current research on ULFOs have been predominantly concentrated on hydro-dominated power systems, with limited exploration into systems where thermal power serves as synchronous sources—let alone elucidation of the underlying mechanisms. This study focuses on regional power grids where wind and thermal power generation coexist. Eigenvalue analysis reveals that frequency regulation control of doubly-fed induction generators (DFIGs) can trigger ULFOs. Leveraging common-mode oscillation theory, an extended system frequency response (ESFR) model incorporating DFIG frequency control is formulated and rigorously validated across a range of operational scenarios. Moreover, frequency-domain analysis uncovers the mechanism by which inertia control affects ULFO behavior, and time-domain simulations are conducted to validate the influence of DFIG control parameters on ULFOs. Full article

With the large-scale integration of wind power, transient stability issues in power systems have become increasingly prominent, among which the impact of the active power recovery rate of wind turbines on system stability cannot be ignored. This paper establishes a sensitivity analytical model between the transient stability index of the system and the active power recovery rate of doubly fed induction generators (DFIGs), revealing the influence of active power recovery rate on system stability. First, the trajectory analysis method is adopted as the transient stability assessment approach, proposing a stability index incorporating accelerating power and transient potential energy. Analytical sensitivity models for synchronous generator accelerating power and transient potential energy to the active power recovery rate of wind turbines are derived in a simplified system. Second, a sensitivity model of the stability margin index to the active power recovery rate is constructed to analyze the influence patterns of the active power recovery rate, initial active power output of wind turbines, and fault duration time on system stability. This research demonstrates that: accelerating the active power recovery rate can restore power balance more quickly but it reduces the rate of transient potential energy variation and delays the peak response of potential energy, thereby decreasing the stability margin; higher initial active power output of wind turbines suppresses the oscillation amplitude of synchronous generators but increases the risk of power imbalance; and prolonged fault duration exacerbates transient energy accumulation and significantly degrades system stability. Additionally, for each 0.1 p.u./s increase in the active power recovery rate of the wind turbine, the absolute value of the stability index of the synchronous machine in the single-machine system decreases by approximately 0.5–1.0, while the sensitivity decreases by approximately 0.01–0.02 s⁻¹. In the multi-machine system, the absolute value of the stability index of the critical machine decreases by approximately 5–10, and the sensitivity decreases by approximately 0.5–1.0 s⁻¹. Full article

With the increasing popularity of low-cost, clean, and environmentally friendly new energy sources, the proportion of grid-connected new energy units has increased significantly. However, since these units are frequency decoupled from the grid through a power electronic interface, they are unable to provide inertia support during active power perturbations, which leads to a decrease in system inertia and reduced frequency stability. In this study, the urgent need to accurately assess inertia is addressed by developing an energy-function-based inertia identification technique that eliminates the effect of damping terms. By integrating vibration mechanics, the proposed method calculates the inertia value after a perturbation using port measurements (active power, voltage phase, and frequency). Simulation results of the Western System Coordinating Council (WSCC) 9-bus system show that the inertia estimation error of the method is less than 1%, which is superior to conventional methods such as rate-of-change-of-frequency (RoCoF) and least squares methods. Notably, the technique accurately evaluates the inertia of synchronous generators and doubly fed induction generators (DFIGs) under virtual inertia control, providing a robust inertia evaluation framework for low-inertia power systems with high renewable energy penetration. This research deepens the understanding of inertial dynamics and contributes to practical applications in grid stability analysis and control strategy optimalization. Full article

This paper introduces a novel fractional-order fuzzy logic controller (FOFLC) designed for stator voltage control in standalone doubly fed induction generator (DFIG) systems used in wind energy applications. Unlike traditional fuzzy logic controllers (FLCs), which are limited by integer-order dynamics, the FOFLC leverages the advanced principles of fractional-order (FO) calculus. By integrating fuzzy logic with fractional-order operators, the FOFLC enhances system precision, adaptability, and interpretability while addressing the inherent limitations of conventional proportional-integral (PI) controllers and integer-order FLCs. A key innovation of the FOFLC is its dual-mode architecture, enabling it to operate seamlessly as either a traditional FLC or a fractional-order FOFLC controller. This versatility allows for independent tuning of fractional parameters, optimizing the system’s response to transients, steady-state errors, and disturbances. The controller’s flexibility makes it particularly well-suited for nonlinear and dynamically complex stand-alone renewable energy systems. The FOFLC is experimentally validated on a 3-kW DFIG test bench using the dSPACE-1104 platform under various operating conditions. Compared to a conventional PI controller, the FOFLC demonstrated superior performance, achieving 80% reduction in response time, eliminating voltage overshoot and undershoot, reducing stator power and torque ripples by over 46%, and decreasing total harmonic distortion (THD) of both stator voltage and current by more than 50%. These results confirm the FOFLC’s potential as a robust and adaptive control solution for stand-alone renewable energy systems, ensuring high-quality power output and reliable operation. Full article

With the increasing penetration of renewable energy, doubly-fed variable speed pumped storage units (DFVSPSUs) are playing an increasingly critical role in grid frequency regulation. However, traditional PI control struggles to address the control challenges posed by the strong nonlinearity of the units and abrupt operational condition changes. This paper proposes an improved β-incremental generalized predictive controller (β-GPC), which achieves precise rotor-side current control through instantaneous linearization combined with parameter identification featuring a forgetting factor. Simulation results demonstrate that under different power command step changes, the traditional PI controller requires up to approximately 0.48 s to reach a steady state while exhibiting a certain degree of oscillations. In contrast, the enhanced β-GPC controller can stabilize the unit in just 0.2 s without any overshoot or subsequent oscillations. It is evident that the proposed controller delivers a superior regulation performance, characterized by a shorter settling time, reduced overshoot, and minimized oscillations. Full article

The variable-speed operation mode of pumped storage units improves the regulation performance and endows the units with characteristics such as isolation from the power grid, thereby affecting the system stability. This study establishes a detailed mathematical model for the connection of doubly fed induction generator-based variable-speed pumped storage (DFIG-VSPS) to a single-machine infinite bus system under power generation conditions in the synchronous rotation direct-quadrature-zero coordinate system. The introduction of the eigenvalue method to analyze the small-disturbance stability of doubly fed variable-speed pumped storage units and the use of participation factors to calculate the degree of influence of each state variable on the small-disturbance stability of the units are innovations of this study. The participation factor enhances flexibility, continuity, and efficiency in doubly fed variable-speed pumped storage by optimizing dynamic power paths and enabling multi-objective control coordination. While eigenvalue analysis is not new, this study is the first to apply it with participation factors to DFIG-VSPS, addressing gaps in prior simplified models. Furthermore, based on the changes in the characteristic root trajectories, the influence of changes in the speed control system parameters and converter controller parameters on the system stability was determined. Finally, the conclusions obtained were verified through simulation. The results indicate that increasing the time constant of water flow inertia poses a risk of system instability, and the increase in proportional parameters and decrease in integral parameters of the power outer loop controller significantly affect the system stability. Full article

This paper investigates the performance of a five-phase silicon carbide (SiC)-based current-source converter (CSC) integrated with a Doubly Fed Induction Generator (DFIG) for wind energy applications. The study explores both healthy and faulty operation, focusing on system behavior under transient conditions and various load scenarios in stand-alone mode. A novel five-phase space vector PWM strategy in dual coordinate planes is introduced, which enables stable control during normal and open-phase fault conditions. Experimental results demonstrate improved stator voltage and current quality, particularly in terms of reduced Total Harmonic Distortion (THD), compared to traditional voltage-source converter-based systems. Furthermore, the system maintains operational stability under a single-phase open fault, despite increased oscillations in stator quantities. The results highlight the potential of five-phase CSC-DFIG systems as a robust and efficient alternative for wind power plants, particularly in configurations involving long cable connections and requiring low generator losses. Future work will focus on enhancing fault-tolerant capabilities and expanding control strategies for improved performance under different operating conditions. Full article

The sub-synchronous oscillation (SSO) characteristics and suppression strategies of a hybrid system comprising doubly fed induction generator (DFIG)-based wind turbines and synchronous pumped storage units connected to the power grid via series-compensated transmission lines are analyzed. A modular modeling approach is used to construct a detailed system model, including the wind turbine shaft system, DFIG, converter control system, synchronous machine, excitation system, power system stabilizer (PSS), and series-compensated transmission lines. Eigenvalue calculation-based small-signal stability analysis is conducted to identify the dominant oscillation modes. Suppression measures are also developed using relative participation analysis, and simulations are carried out to validate the accuracy of the model and analysis method. The analysis results indicate that the SSO phenomenon is primarily influenced by the electrical state variables of the DFIG system, while the impact of the state variables of the synchronous machine is relatively minor. When the level of series compensation in the system increases, SSO is significantly exacerbated. To address this issue, a sub-synchronous damping controller (SSDC) is incorporated on the rotor side of the DFIG. The results demonstrate that this method effectively mitigates the SSO and significantly enhances the system’s robustness against disturbances. Furthermore, a simplified modeling approach is proposed based on relative participation analysis. This method neglects the dynamic characteristics of the synchronous machine while considering its impact on the steady-state impedance and initial conditions of the model. These findings provide theoretical guidance and practical insights for addressing and mitigating SSO issues in hybrid renewable energy systems composed of DFIGs and synchronous machines. Full article

The present study investigates the control strategy of a novel doubled-fed induction generator (DFIG) with a series grid-side converter (SGSC) during grid faults. The rotor-side inverter is subject to a control strategy derived from the Model Predictive Current Control (MPCC) theory, which is implemented during periods of fault occurrence; for the series grid-side converter, the positive and negative sequence component control is implemented during both steady state and fault periods to enhance system stability and performance. The proposed coordinated control strategy is implemented on a doubly fed turbine with SGSC, while taking into account different degrees of symmetric and asymmetric faults to further evaluate the efficacy of the proposed method. The results of the simulations demonstrate the efficacy of the model-predictive current control scheme applied to the rotor-side converter under conditions of asymmetric faults. This enables the suppression of a range of phenomena, including rotor overcurrent, stator overcurrent, and overvoltage, electromagnetic torque ripple, and DC bus voltage during low-voltage ride-through (LVRT), among others. The present study confirms the viability of implementing positive and negative sequences of voltage separation control in the SGSC during both grid faults and steady state. This approach is expected to minimize the switching of SGSC control strategies and thereby reduce output power fluctuations. The Rotor Side Converter (RSC) and SGSC can perform coordinated control during faults, and the proposed method is able to improve low-voltage ride-through performance compared to existing methods, thereby preventing damage to the converter under multiple fault conditions. Full article

The integration of renewable energy sources, such as wind power, into the electrical grid is essential for the development of sustainable energy systems. Doubly fed induction generators (DFIGs) have been significantly utilized in wind energy conversion systems (WECSs) because of their efficient power generation and variable speed operation. However, optimizing wind power extraction at variable wind speeds remains a major challenge. To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). The DFIG is controlled via field-oriented control (FOC), which allows independent power output regulation and separately controls the stator active and reactive power components. Through its compact design, bidirectional power flow, and enhanced harmonic performance, the MC, which is controlled by the simplified Venturini modulation technique, improves the efficiency and dependability of the system. Simulation outcomes confirm that the ANN-based MPPT enhances the power extraction efficiency and improves the system performance. This study shows how wind energy systems can be optimized for smart grids by integrating advanced control techniques like FOC and simplified Venturini modulation with intelligent algorithms like ANN. Full article