Fed Induction Generator Research Articles

Artificial intelligent fuzzy control and LAPO algorithm for enhancement LVRT and power quality of grid connected PV/wind hybrid systems

Low Voltage Ride Through (LVRT) is considered one of the main and serious problems facing the electrical grid. It occurs due to three-phase symmetric faults and asymmetric faults such as a double line to ground fault that applies in this system. This paper applies Static Synchronous Compensators (STATCOM) to improve the LVRT capability and dynamic performance of an electrical grid linked to a Photovoltaic (PV)/Wind hybrid system through grid disturbances. A hybrid power system containing a PV station that produces 1 MW and a wind farm from type Doubly Fed Induction Generator (DFIG) that produces 9 MW is connected to STATCOM with 48 pulses at PCC bus and energized load. It compensates reactive power to improve LVRT that occurred due to fault. The applied STATCOM controller adjusts the voltage of the PCC bus during an occuring fault on the grid by compensating reactive power. STATCOM is controlled by a Proportional–Integral–Derivative (PID) and is compared with STATCOM controlled by Artificial Intelligence Control (AIC)-based on Proportional—Integral Fuzzy Logic Control (PI FLC). The Lightning Attachment Procedure Optimization Algorithm (LAPO) optimization method is used to adjust the parameters of the PI controller to reduce error signals. A simulation model of the suggested hybrid power system has been performed using Matlab/Simulink. The simulation results of STATCOM proved powerful and the effectiveness of STATCOM with PI FLC in reducing voltage dip, compensating active power of wind and PV farm, protecting DC-link voltage of PV and wind from overvoltage and oscillation that happens at three-phase fault and double line to ground fault as compared with PID STATCOM in enhancement LVRT capability, and power quality.

Modeling, Control Study, and Power Management Strategy of a Hybrid Grid-Connected AC/DC Microgrid with High Integration of Renewable Energies and Green Hydrogen Sources

Abstract This first quarter of the 21st century is increasingly marked by population growth, digital and industrial de- velopments, growing need for electricity supply, and climate change. All this, to name just a few, have made the establishment of a stable, flexible, controlled, well-designed, extensive and clean power system a necessity. Conse- quently, distributed microgrid generation based on alternative/renewable energies and/or low-carbon technologies has emerged. In this paper, we study the modeling, the control, and the power management strategy of a grid-connected hybrid Alternating/Direct Current (AC/DC) microgrid based on a wind turbine generation system using doubly fed induction generator, a photovoltaic generation system, and storage elements including hydrogen storage system and batteries. Adequate modeling is described, and the overall system monitoring is presented and applied to manage appropriate power sharing and to control active and reactive powers, in order to match load and weather fluctuation behaviour. Simulations are carried out using MATLAB/Simulink simulation tool. Simulations reveal convenient re- sults in terms of the bidirectional interlinking converter capabilities regarding power balance establishment between the two subgrids, reactive power compensation to ensure a unity power factor, and DC-bus voltage regulation at 1200 V. In addition, the primary and secondary controls are approved for each distributed generation of the studied system to attain the assigned power references, regardless of whether the subgrid is heavily or lightly loaded throughout the four considered case studies, showing satisfactory tracking and interacting performances, and thus stimulating a stable system implementation.

Probabilistic Robust Damping Controller Optimization for Mitigating Subsynchronous Control Interaction in DFIG and PMSG‐Based Wind Farms

ABSTRACTAdvanced control and mitigation solutions are required due to the enormous challenges posed by sub‐synchronous control interaction in wind farms. These concerns include system instability, potential damage to turbines, and grid stability issues. This research presents the probabilistic robust damping controller, an adaptive control approach, to address the issues in grid‐connected wind farms. The innovation employs the balanced remora optimization algorithm to optimize controller parameters, ensuring system stability under various conditions. For permanent magnet synchronous generator‐based wind farms with weak grid circumstances, critical elements such as the DC‐link voltage, the d‐q axis current reference, and the actual values in the grid‐side converter are essential for problem mitigation. The controller generates controlled output using these input signals. The MATLAB‐based implementation demonstrates the controller effectiveness in damping issues within a series‐compensated doubly fed induction generator. Comparative analysis with conventional controllers under different grid conditions and disturbances validates its superior performance. Time‐domain simulations, both with and without time delay, further confirm the controller's ability to enhance system stability and dampen the issues. Four schemes are used to evaluate the doubly fed induction generator‐based wind farms: wind speed at 13 m/s with 75% series compensation, 7 m/s with 75% compensation, 9 m/s with 45% compensation, and 9 m/s with 60% compensation. Under short circuit ratio, the wind farms based on permanent magnet synchronous generators are analyzed in three scenarios: normal, strong, and weak cases.

Ancillary Services to Mitigate Non-linear and Unbalanced Load Based on CPT Using a DFIG Power Plant

The increase of renewable energy sources and non-linear loads on the utility grid introduces challenges in maintaining the nominal conditions of the utility grid. A viable approach to addressing some of these challenges is to utilize renewable energy conversion systems that accomplish supplementary functions in addition to supplying active power. This paper presents the implementation of ancillary services to mitigate non-linear and unbalanced loads using a single Doubly Fed Induction Generation (DFIG) power plant. For this, the Conservative Power Theory (CPT) is used to provide three types of services simultaneously: active filtering, reactive power compensation, and unbalanced phase compensation. A back-to-back converter is used to control the power flow in the DFIG and employ ancillary services. Two control strategies are compared: in the dq reference frame and the $\alpha \beta$ reference frame. Simulations in MatLab/Simulink are used to evaluate the response of the CPT and the control strategies. The ancillary services performance is analyzed using the indicator based on standards and CPT factor. The results show that the indicators comply with the standards depending on the active power supply. Moreover, $\alpha\beta$ reference frame exhibits better performance than $dq$ reference frame.

Theoretical and experimental analysis of unbalanced doubly fed induction generators

In this paper, a novel approach has been developed for the modeling and analysis of doubly fed induction generators operating under unbalanced load conditions. This comprehensive approach considers the derivation of the doubly fed induction generator’s neutral voltage during unbalanced conditions. Using this innovative approach, important and extremely precise signatures on stator currents and voltages have been extracted during a rational simulation time. It has been shown that for unbalanced conditions, an abnormal operation is produced. It is characterized by unbalanced stator voltages, currents, and specific harmonics through the stator variables. These harmonics have been proposed to detect unbalanced conditions. The consistency and reliability of this approach for the analysis and modeling of unbalanced doubly fed induction generators are validated by the coherence and good correlation between experimental and simulation results.

Performance analysis of cascaded doubly fed induction generator with matrix converter for wind power conversion systems

Performance analysis of cascaded doubly fed induction generator with matrix converter for wind power conversion systems

Stochastic stability analysis method for doubly fed generator sets considering random blade stress

AbstractWith the increasing capacity of doubly fed induction generators (DFIGs), the diameter of the wind turbine is increasing, the blades are getting longer and longer, and in the process of power generation, the tower shadow effect as well as the role of wind shear are more obvious, and the random blade stresses caused by this is also getting bigger. Random blade stresses cause random and cyclic fluctuations in the power generated by the wind turbine, and power fluctuations often cause voltage flicker, which affects the control system and power quality. To address the impact of random blade stresses on the grid‐connected stability of DFIG, the results of the traditional stability analysis methods may be too conservative or lead to too high a dimensionality to be analyzed. To solve the above problems, this paper proposes a grid‐connected stochastic stability analysis method for DFIG sets considering random blade stresses based on the stochastic averaging method under the Hamiltonian system. a stochastic dynamics model of the doubly fed wind farm was established by considering random blade stress. Subsequently, using the proposed generalized Hamiltonian principle, the model and energy functions in the proposed Hamiltonian form H, based on the stochastic averaging method (SAM), were established to obtain the system energy diffusion equation. Probability density function and regional stability probability were obtained from explicit expressions of the mean and regression square root processes. The drift and diffusion coefficients were obtained using the SAM, and the backward Kolmogorov equation was derived from the Ito equation to obtain the conditional reliability function and the probability density of the first crossing time. Finally, the effects of torque fluctuations with different stochastic intensities on the grid‐connected stability of doubly fed wind farms were investigated, and the effectiveness of the proposed generalized Hamiltonian SAM applied to the stochastic stability analysis of DFIG was verified by numerical analysis and Monte Carlo simulation. This provides a theoretical foundation for analyzing the grid‐connected stability of DFIG affected by random blade stresses.

SSO optimized FOFPID regulator design for performance enhancement of doubly fed induction generator based wind turbine system.

A wind turbine system (WTS) is a highly coupled and nonlinear system where the output power depends upon highly uncertain wind speed. Therefore, the quality of produced power becomes a challenging problem for researchers. Direct Vector Control (DVC) is a powerful and widely utilized power control strategy to deal with winds that vary rapidly and randomly. As a result, this article employed the newly developed Social Spider Optimization (SSO) technique to optimize the design parameters of Fractional-Order Fuzzy Proportional-Integral with Derivative (FOFPID) regulator to maintain the output power of the studied DFIG-based WTS at the rated value under dynamic wind conditions. The suggested FOFPID controller integrates the capabilities of the Fuzzy intelligent regulator and the Fractional-Order controller, enhancing DFIG current control while allowing independent control of active and reactive power. The approach is incorporated within the DVC strategy of the DFIG's rotor-side converter (RSC), replacing the conventional Proportional-Integral (PI) regulator in the internal current loops. Extensive performance evaluations are conducted under various operating conditions, including active power reference changes, parameter uncertainties, and rapid wind speed variations. Comparative analyses with SSO-optimized PID and Fuzzy regulators show that the FOFPID regulator performs better in terms of maximum overshoot, extreme undershoot, settling time, Total Harmonic Distortion (THD), and Weighted Total Harmonic Distortion (WTHD). The suggested FOFPID regulator also displays stronger robustness against parameters mismatch and weather change than other regulator architectures.

Installation and Management of Regulation Systems of a Hydroelectric Power Plant with Doubly Fed Induction Generator and Results of a Case Study

Installation and Management of Regulation Systems of a Hydroelectric Power Plant with Doubly Fed Induction Generator and Results of a Case Study

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.

Inertia enhancement for doubly fed induction generators with comprehensive inertia control and enhanced phase-locked loop regulation

As the penetration of wind power in the power system gradually increases, it becomes increasingly urgent to utilize the inertial response capability of DFIGs to participate in system frequency support. However, the existing inertial control technology is based on converters, which has problems such as slow response speed and inability to exert the regulation potential fully. To address this issue, this paper proposes a control architecture based on phase-locked loop (PLL) inertial feedback aimed at enhancing the inertia response capability of DFIGs. Initially, the paper formulates a model for DFIG inertia response based on intrinsic controllers, meticulously examining its characteristics. Subsequently, an inertia control mechanism is integrated into the PLL controller, outlining a refined control framework that enhances inertia response compared to conventional approaches. On this basis, the impact of controller parameters on inertia is analyzed, revealing their changing trends. The results of the analysis contribute to understanding and optimizing the inertia response capability of DFIGs. Finally, the efficacy of the proposed methodology is substantiated by the IEEE 39-bus system simulation.

Fuzzy Logic-Enhanced Direct Power Control for Wind Turbines with Doubly Fed Induction Generators

Fuzzy Logic-Enhanced Direct Power Control for Wind Turbines with Doubly Fed Induction Generators

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.

Fuzzy Logic-Based Smart Control of Wind Energy Conversion System Using Cascaded Doubly Fed Induction Generator

This paper introduces a robust system designed to effectively manage and enhance the electrical output of a Wind Energy Conversion System (WECS) using a Cascaded Doubly Fed Induction Generator (CDFIG) connected to a power grid. The solution that was investigated is the use of a CDFIG that is based on a variable-speed wind power conversion chain. It comprises the electrical and mechanical connection of two DFIGs through their rotors. The originality of this paper lies in the innovative application of a fuzzy logic controller (FLC) in combination with a CDFIG for a WECS. To demonstrate that this novel configuration enhances control precision and performance in WECSs, we conducted a comparison of three different controllers: a proportional–integral (PI) controller, a fractional PID (FPID) controller, and a fuzzy logic controller (FLC). The results highlight the potential of the proposed system in optimizing power generation and improving overall system stability. It turns out that, according to the first results, the FLC performed optimally in terms of tracking and rejecting disturbances. In terms of peak overshoot for power and torque, the findings indicate that the proposed FLC-based technique (3.8639% and 6.9401%) outperforms that of the FOPID (11.2458% and 10.9654%) and PI controllers (11.4219% and 11.0712%), respectively. These results demonstrate the superior performance of the FLC in reducing overshoot, providing better control stability for both power and torque. In terms of rise time, the findings show that all controllers perform similarly for both power and torque. However, the FLC demonstrates superior performance with a rise time of 0.0016 s for both power and torque, compared to the FOPID (1.9999 s and 1.9999 s) and PI (0.0250 s and 0.0247 s) controllers. This highlights the FLC’s enhanced responsiveness in controlling power and torque. In terms of settling time, all three controllers have almost the same performance of 1.9999. An examination of total harmonic distortion (THD) was also employed to validate the superiority of the FLC. In terms of power quality, the findings prove that a WECS based on an FLC (0.93%) has a smaller total harmonic distortion (THD) compared to that of the FOPID (1.21%) and PI (1.51%) controllers. This system solves the problem by removing the requirement for sliding ring–brush contact. Through the utilization of the MATLAB/Simulink environment, the effectiveness of this control and energy management approach was evaluated, thereby demonstrating its capacity to fulfill the objectives that were set.

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.

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.

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.

An improved dual vector control for a doubly fed induction generator based wind turbine during asymmetrical voltage dips

An improved dual vector control for a doubly fed induction generator based wind turbine during asymmetrical voltage dips