Search Results (456)

An active damping control technique based on improved linear active disturbance rejection control (LADRC) is suggested to address the inadequate damping of doubly fed induction generator (DFIG) systems coupled to the grid using series compensation capacitors. Conventional LADRC still has certain limitations under complicated operating conditions, primarily because of its inadequate periodic disturbance estimate capabilities, which limit the system’s dynamic performance and disturbance-rejection capability. An enhanced LADRC scheme is created for the inner current loop of the rotor-side converter (RSC) in the DFIG system in order to lessen these restrictions. To enable a real-time estimate and adjustment of sub-synchronous disturbances, a decoupled linear extended state observer (LESO) is first proposed. In order to effectively attenuate both sub-synchronous oscillation and periodic disturbances, a composite control structure with enhanced suppression capability is constructed by incorporating an improved repetitive control scheme into the linear state error feedback law. The results show that the improved LADRC significantly enhances damping performance and disturbance rejection capability in the subsynchronous frequency range, suppressing active power oscillations within approximately 0.3 s based on a ±10% settling band. Compared with the conventional LADRC, the average THD of the grid current is reduced from 3.43% to 0.56%. Full article

To address the key problems of low-frequency oscillation and insufficient regulation accuracy at the Point of Common Coupling (PCC) in hydro–wind–photovoltaic hybrid systems, which are caused by the randomness of wind and photovoltaic output, the water-hammer effect of hydropower units, and multi-source power coupling, a joint control strategy based on Fractional-Order Proportional Integral Derivative (FOPID) and Co-evolutionary Multi-objective Particle Swarm Optimization (CMOPSO) is proposed. First, a small-signal transfer function model of the system covering photovoltaic inverters, doubly fed induction generators (DFIGs), hydropower units and voltage-source converter-based high-voltage direct current (VSC-HVDC) converter stations is established to accurately characterize the water-hammer effect and multi-source dynamic coupling characteristics. Second, a Caputo-type FOPID controller is designed. Compared with traditional integer-order controllers with limited tuning flexibility, the FOPID controller utilizes its five degrees of freedom to address specific multi-source coupling challenges. This precisely compensates for the non-minimum phase lag caused by the water-hammer effect in hydropower units via the fractional derivative link, and effectively smooths the impact of stochastic wind–solar fluctuations on PCC voltage through the memory characteristics of the fractional integral link. This multi-parameter regulation mechanism prevents a trade-off between response speed and overshoot suppression, achieving effective decoupling of complex multi-source dynamic interactions. Third, a dual-objective optimization framework with the Integral of Time-weighted Absolute Error (ITAE) and Oscillatory Disturbance Risk Index (ODRI) as the objectives is constructed. The multi-population co-evolution mechanism of the CMOPSO algorithm is adopted to solve the Pareto-optimal solution set, realizing the coordinated optimization of dynamic response accuracy and oscillation instability risk. Finally, comparative simulations are carried out on the Simulink platform with traditional PI/FOPI controllers and optimization algorithms such as Multi-objective Particle Swarm Optimization based on the Decomposition/Simple Indicator-Based Evolutionary Algorithm (MPSOD/SIBEA). The results show that the proposed strategy can effectively suppress low-frequency oscillations in the range of 0~30 Hz. Compared with the traditional PI controller, the PCC voltage overshoot is reduced by more than 40%, the oscillation decay time is shortened by 33%, the ITAE and ODRI indices are decreased by 12.58% and 2.47%, respectively, and the stability of DC bus voltage is significantly improved. Its robustness and comprehensive control performance are superior to existing methods, providing an efficient and stable control scheme for power electronics-dominated complex new energy grid-connected systems. Full article

Wind-storage coordinated frequency regulation enhances the frequency stability of large-scale wind power systems. However, existing methods often rely on fixed parameters, limiting adaptability and accelerating energy storage depletion. To address these limitations, a coordinated control strategy based on dynamic weighting coefficients and model predictive control (MPC) is proposed. First, a dynamic weighting mechanism is designed to adaptively adjust the contributions of virtual inertia and droop control based on the system frequency state and the energy storage system’s (ESS) state of charge (SOC), thereby avoiding abrupt power variations and maintaining the SOC within safe limits. Second, an MPC-based rolling optimization model is established to continuously allocate the active power outputs between the doubly fed induction generator (DFIG) and the ESS, aiming to minimize both frequency deviations and regulation costs. Simulation results demonstrate the superiority of the proposed strategy. Under a step load disturbance, the maximum frequency deviation is reduced by 11.3%, and the peak time is shortened by 13% compared to conventional droop control. Furthermore, under continuous load fluctuations, the proposed approach significantly mitigates SOC depletion and minimizes system frequency fluctuations, proving its effectiveness in enhancing the frequency resilience of wind-storage combined systems. Full article

Ensuring frequency security is of vital importance for power systems. As the penetration of renewable energy generation (REG) continues to increase, its impact on frequency stability cannot be neglected. The motion equation model is a suitable modeling method for REGs, which can derive a model with a structure similar to synchronous generators. However, when using the motion equation models for frequency dynamic analysis, only the impact paths related to active power disturbance are retained. Adding that there are different types of motion equation models, it is important to discuss which type is more appropriate. This paper takes the doubly fed induction generator-based wind turbine as an example; two types of motion equation models are first derived and verified. Then, by looking back at the assumptions of the average system frequency model, the adaptability of each model is judged. By comparing the frequency dynamics between different motion equation models and the electromagnetic transient model, the results indicate that the motion equation model employing active power and terminal voltage dynamics as input variables is more suitable for average frequency analysis. Lastly, by utilizing these models in a power system, the analysis is verified through MATLAB/Simulink R2021a. Full article

High penetration of converter-based wind generation reduces system inertia. It poses challenges to frequency stability in modern distribution networks, particularly in doubly fed induction generator (DFIG)-based wind-energy-conversion systems (WECSs), where frequency regulation is coupled with point-of-common-coupling (PCC) voltage and power factor (PF) dynamics. This study presents a multi-objective comparative evaluation of proportional–integral (PI), proportional–integral–derivative (PID), fractional-order PID (FOPID), and adaptive neuro-fuzzy inference system (ANFIS) controllers for a DFIG-based WECS connected to a radial distribution feeder. Controller parameters are tuned using multi-objective optimisation, considering frequency deviation, overshoot, settling time, disturbance robustness, control smoothness, and computational cost, while maintaining PCC voltage and PF within acceptable limits. MATLAB/Simulink simulations are conducted under turbulent wind conditions, load variations, voltage disturbances, and measurement noise. The results indicate that conventional PI and PID controllers exhibit limited performance under low-inertia conditions, whereas FOPID improves damping and voltage/PF behaviour. ANFIS achieves the best overall performance, providing reduced frequency deviation, faster settling time (below 3 s), improved disturbance rejection, and significantly lower integral absolute error (up to ~90%) compared to PI control. These findings offer practical guidance for selecting and tuning controllers to enhance frequency-centric stability in wind-integrated distribution networks. Full article

With the large-scale integration of wind power, modern power systems are facing reduced equivalent inertia, weakened primary frequency regulation capability, and insufficient coordination between wind turbines and energy storage during joint frequency support. To address these issues, this paper investigates a wind–storage hybrid system composed of doubly fed induction generators (DFIG) and supercapacitor energy storage and proposes a coordinated primary frequency regulation strategy combining fuzzy logic control (FLC) and model predictive control (MPC). Considering the variations in rotor kinetic energy reserve and frequency support capability under different wind speed regions, a coordinated regulation mechanism is developed for multiple operating conditions. In addition, a variable-coefficient synthetic inertia control scheme with rotor speed safety constraints is designed to adaptively adjust the turbine regulation coefficients, while an SOC-feedback-based adaptive virtual droop strategy is introduced to improve the sustained support capability of the energy storage unit. On this basis, a multi-objective model predictive control framework is established to optimize the reference power allocation between the wind turbine and the energy storage unit in a rolling manner. The proposed method is characterized by three coordinated features, namely, multi-region wind–storage frequency regulation, rotor-speed-safe adaptive support of the wind turbine and SOC-aware adaptive support of the storage unit, as well as MPC-based rolling power allocation. Simulation results show that the proposed strategy improves the frequency nadir, reduces the steady-state frequency deviation, and enhances coordinated power sharing, thereby improving the primary frequency regulation performance and overall frequency stability of the wind–storage hybrid system. Full article

In this paper, a short-term active power curtailment (ST-APC) strategy for doubly-fed induction generator (DFIG) wind farms is proposed to enhance first-swing rotor angle stability under fault disturbances. While wind power is a clean renewable resource that is widely deployed, its large-scale integration heightens concerns about transient stability. After analyzing DFIG operating principles, this study advocates for using short-horizon active power control to mitigate the adverse stability impacts of wind farms. Using the Western System Coordinating Council (WSCC) three-machine nine-bus test system, the effectiveness of the ST-APC strategy across diverse operating conditions was verified. This study is based on the fundamental principle that reducing the output of wind turbines is required for first-swing stability after faults to increase the kinetic energy of synchronous machines. A closed-loop control strategy combining voltage drop, frequency change, and a timer is designed. The correlation laws between various control parameters such as control activation timing, duration, and modulation depth and first-swing stability are analyzed, providing references for parameter selection in engineering applications. The findings indicate that the proposed strategy is practical and adaptable, making it suitable for power systems with high wind power penetration. Full article

The increasing penetration of Doubly Fed Induction Generator (DFIG)-based wind energy systems raises major concerns regarding voltage stability and Fault Ride-Through (FRT) capability under grid disturbances and wind speed variations. This paper proposes a coordinated control framework for a grid-connected DFIG system, where a Static Synchronous Compensator (STATCOM) based on discrete-time deadbeat current control is integrated with a Supercapacitor Energy Storage System (SCES) connected to the DC link through a bidirectional DC-DC converter governed by cascaded Active Disturbance Rejection Control (ADRC). The deadbeat-controlled STATCOM provides fast reactive current injection for voltage support during sag and swell events, while the cascaded ADRC enhances DC-link voltage regulation and suppresses rotor-speed oscillations. Comprehensive MATLAB/Simulink simulations are carried out under variable wind speed and severe grid disturbances up to 80% voltage sag and 50% voltage swell. For voltage regulation, the proposed method is compared with SVC and PI-based STATCOM. In addition, SCES control performance is evaluated by comparing PI, single ADRC, and cascaded ADRC in terms of DC-link voltage overshoot, undershoot, and ripple. The results show clear improvements in voltage response and transient performance. Under a 20% voltage sag, the proposed deadbeat-controlled STATCOM significantly improves the dynamic response, where the undershoot is reduced from 0.125 p.u. (with SVC) to 0.04 p.u., and the settling time is shortened from 0.04 s to 0.025 s. Under a severe 80% sag, the overshoot is limited to 0.02 p.u., compared with 0.13 p.u. for the SVC and 0.15 p.u. for the PI-based STATCOM. Similarly, under a 50% voltage swell, the overshoot is reduced to 0.20 p.u., compared with 0.46 p.u. for the SVC and 0.27 p.u. for the PI-based STATCOM. Regarding the DC-link performance under 80% sag, the proposed cascaded ADRC-based SCES limits the overshoot and undershoot to 6 V and 2 V, respectively, compared with 39 V and 32 V for the PI-based SCES. These results confirm the superior damping, disturbance rejection, and FRT enhancement achieved by the proposed strategy. Full article

This paper presents an intelligent cascaded fractional-order proportional–integral (CFO-PI) control strategy optimized using a genetic algorithm (GA) for a 1.5 MW DFIG-based multi-rotor wind turbine (MRWT) system. The primary objective is to enhance operational performance and power quality. The proposed method is evaluated against the conventional direct power control scheme using a traditional PI regulator (DPC-PI) to demonstrate its effectiveness. Comparative analysis shows substantial performance improvements achieved by the CFO-PI approach. Specifically, active power ripple is reduced by 61.71% compared to DPC-PI, resulting in smoother power delivery and improved grid compatibility. In addition, the steady-state error of active power decreases by 72.60%, indicating improved tracking accuracy. For reactive power, a 52.03% reduction in ripple is observed, while current ripple is reduced by approximately 56%, reflecting enhanced waveform quality. These results highlight the CFO-PI controller’s capability to maintain better power quality and steady-state performance relative to conventional DPC-PI. Overall, the GA-optimized CFO-PI controller provides a promising alternative for improving dynamic performance and power quality in DFIG-based MRWT systems. Full article

High wind power penetration aggravates power system inertia scarcity, and wind turbines switching to MPPT mode after virtual inertia support induces secondary frequency drop (SFD), impairing grid frequency stability. Traditional energy storage system (ESS) sizing methods fail to couple wind turbine virtual inertia dynamics, rotor kinetic energy recovery and time-varying wind speeds, causing a trade-off between regulation performance and economy. To address this, an optimal ESS sizing method for wind-storage coordinated frequency regulation is proposed, including a doubly fed induction generator (DFIG) model for virtual inertia-power drop correlation, an incomplete compensation strategy, and a constrained three-objective optimization model co-optimizing virtual inertia and ESS parameters. The method, solved by NSGA-II with fuzzy membership functions, is validated on a 1000 MVA grid with a 245 MW DFIG wind farm. Results show it mitigates SFD, avoids ESS over-sizing, and balances performance and economy, breaking the decoupling between traditional ESS sizing and the virtual inertia dynamics of wind turbines. Full article

The increasing penetration of wind energy is a key enabler of the global transition toward low-carbon and sustainable power systems. However, ensuring high efficiency, power quality, and operational reliability under variable wind and grid conditions remains a critical challenge for doubly fed induction generator (DFIG)-based wind energy conversion systems. Conventional direct power control (DPC) strategies based on proportional–integral (PI) regulators are simple and widely implemented, yet their performance degrades in the presence of nonlinear system dynamics, parameter uncertainties, and rapid wind speed fluctuations—factors that directly affect energy yield, component lifetime, and grid stability. To enhance the sustainability and resilience of wind power generation, this study proposes a cascaded neural network-based control architecture for DFIG-driven systems. The outer neural control loop regulates active and reactive power references to optimize energy capture and support grid requirements, while the inner neural loop ensures fast and precise tracking by generating appropriate control signals for the rotor-side converter. Leveraging their adaptive learning capability, the neural controllers effectively model nonlinear dynamics and compensate for uncertainties in real time. Compared with the conventional DPC-PI scheme, the proposed approach achieves improved dynamic response, reduced power and electromagnetic torque ripples, enhanced disturbance rejection, and greater robustness under varying wind and grid conditions. These improvements contribute to sustainable energy production by increasing conversion efficiency, reducing mechanical stress, minimizing maintenance requirements, and extending turbine service life. Furthermore, improved reactive power control enhances grid integration and supports stable operation in renewable-dominated power systems. Simulation results validate the superior performance of the cascaded intelligent control strategy. The findings demonstrate that advanced adaptive control techniques can play a significant role in strengthening the reliability, efficiency, and long-term sustainability of wind energy systems, thereby supporting global decarbonization goals and the broader transition to sustainable energy infrastructures. Future work will focus on real-time implementation, stability assessment, and experimental validation to facilitate practical deployment. Full article

This paper investigates the effectiveness of integrating a matrix converter (MC) into a wind turbine system based on a Doubly Fed Induction Generator (DFIG), focusing on the indirect control of active and reactive power using fractional regulators. To evaluate the performance of this architecture, three distinct configurations are studied and compared: (i) a conventional system using an AC-DC-AC converter combined with a conventional PI regulator, (ii) a structure integrating a matrix converter with a PI regulator, and (iii) an advanced combination of MC with a fractional regulator. Simulation results demonstrate that this latter solution offers significant improvements in dynamic performance, more precise regulation of active and reactive power, and higher energy efficiency than the other two methods. Full article

Sub-synchronous oscillations (SSOs) induced by the interaction between doubly fed induction generators (DFIGs) and weak grids pose a critical threat to the grid-connected stability of DFIG-based wind power systems. In this paper, a dual-damping-term compensation filter based on the concept of motion-induced amplification (MIA), together with an optimized design method using a linear quadratic regulator (LQR), is applied to the DFIG system. The effectiveness of the proposed approach in suppressing DFIG shafting oscillations and mitigating grid-connected frequency coupling is verified, and the underlying mechanisms are thoroughly investigated. By establishing a shafting dynamics model for the DFIG and a frequency-coupled oscillation impedance model, this study focuses on revealing the differentiated impacts of the dual damping parameters (${\mathrm{Z}}_{\mathrm{p}}$ and ${\mathrm{Z}}_{\mathrm{q}}$) on system stability under two operating modes: maximum power point tracking (MPPT) and constant power operation. Stability analysis based on the generalized Nyquist criterion (GNC), together with time-domain simulations, demonstrates that coordinated optimization of the dual damping terms can effectively suppress shafting oscillations and frequency coupling, thereby significantly enhancing the grid-connected stability of DFIG systems. Full article

Doubly Fed Induction Generators (DFIGs) are widely employed in variable-speed wind turbine systems due to their high efficiency, enhanced controllability, and economic viability. This paper presents an intelligent neural-network-based control strategy aimed at maximizing wind energy extraction while ensuring accurate speed regulation of a DFIG by continuously tracking the maximum power point under fluctuating wind conditions. Two independent control schemes are developed for the decoupled regulation of active and reactive power in a grid-connected DFIG wind turbine. The first scheme is based on conventional field-oriented control using proportional integral regulators (FOC–PI), while the second employs an Artificial Neural Network Controller (ANNC). The effectiveness of both controllers is evaluated through MATLAB/Simulink 2020 Version simulations of a 1.5 MW DFIG-based wind energy conversion system and experimentally validated using a real wind profile implemented on an eZdsp TMS320F28335 digital signal processor. The proposed control approach achieves low output ripple, a steady-state error below 0.16%, total harmonic distortion of 0.38%, and a limited overshoot of 5%. The obtained results confirm the robustness and reliability of the implemented control strategies in enhancing power capture and improving overall system stability under variable wind conditions. Full article

To address the low-voltage fault issue in doubly fed induction generator-motor (DFIGM) systems, this paper proposes a practically implementable cooperative control strategy that integrates an improved current reversely tracking control (CRTC) scheme with an enhanced IGBT-based active crowbar topology. The proposed method optimizes the current-tracking coefficients under rotor voltage and current constraints during LVRT operation. Meanwhile, the enhanced active crowbar provides reactive power support, thereby suppressing negative-sequence current components, mitigating harmonic distortion, and improving the power quality at the point of common coupling (PCC). A 10-MW DFIGM model is developed, and comparative studies are conducted with the conventional inductance emulating control (IEC) and the crowbar structure. The experimental results show the feasibility and effectiveness of the proposed method. Full article