Doubly Fed Induction Generator Research Articles

Fuzzy logic based improved direct torque control of DFIG-based wind turbines

This paper investigates direct torque control with a fuzzy controller (F-DTC) for a two-level voltage source inverter feeding the rotor of a doubly-fed induction generator (DFIG) based on a variable-speed wind energy conversion system (VSWECS). The wind turbine's MPPT technology is used to obtain the torque reference. The proposed fuzzy logic-based direct torque control (F-DTC) is designed to eliminate the flux and electromagnetic torque ripples that are common with existing (DTC) controls, leading to smoother operation and improved efficiency in the wind energy conversion system. The fuzzy logic controller improves switching decision-making by handling uncertainties and non-linearities, resulting in smoother and more efficient control of the torque and flux. To validate the effectiveness of the proposed F-DTC method, simulations are conducted in MATLAB/SIMULINK, and the results are compared with those of the classical DTC approach. The findings demonstrate that the F-DTC strategy significantly reduces torque and flux ripples, enhances the dynamic response, and improves overall system performance.

Regulation of Active and Reactive Powers in Doubly-Fed Induction Generators Utilizing Proportional-Integral and Artificial Neural Network Controllers

Regulation of Active and Reactive Powers in Doubly-Fed Induction Generators Utilizing Proportional-Integral and Artificial Neural Network Controllers

An Improved Collaborative Control Scheme to Resist Grid Voltage Unbalance for BDFG-Based Wind Turbine

This article presents an improved collaborative control to resist grid voltage unbalance for brushless doubly fed generator (BDFG)-based wind turbine (BDFGWT). The mathematical model of grid-connected BDFG including machine side converter (MSC) and grid side converter (GSC) in the αβ reference frame during unbalanced grid voltage condition is established. On this base, the improved collaborative control between MSC and GSC is presented. Under the control, the control objective of the whole BDFGWT system, including canceling the pulsations of electromagnetic torque and the unbalance of BDFGWT’s total currents, pulsations of BDFGWT’s total powers are capable of being realized; therefore, the control capability of BDFGWT to resist unbalanced grid voltage is greatly improved. Moreover, improved single-loop current controllers adopting PR regulators are proposed for both MSC and GSC where the sequence extractions for both MSC and GSC currents are not needed any more, and hence the proposed control is much simpler. In addition, the transient characteristics are also improved. Moreover, in order to achieve the decoupling control of current and average power, current controller also adopts the feedforward control approach. Case studies for a two MW BDFGWT system are implemented, and the results verify that the presented control is capable of effectively improving the control capability for BDFGWT to resist grid voltage unbalance and exhibit good stable and dynamic control performances.

High proportion of new energy power system frequency and voltage support and regulation technology based on doubly fed induction generator

Abstract With the increasing proportion of new energy in power systems, issues regarding system voltage, inertia, and primary frequency regulation have become increasingly severe. In response to control and grid safety issues, a high proportion of new energy power system frequency and voltage support and regulation technology based on a doubly fed induction generator (DFIG) is proposed. The voltage-magnetic link equation of DFIG is theoretically derived, and the control principles of active and reactive power of DFIG are proposed. The support and regulation characteristics of improving the voltage of new energy substations are studied. Verification is conducted through large-scale grid simulation and on-site measurements.

Reactive power and voltage control based on reactive power compensation coefficient and sensitivity factor

Abstract Aiming at the problems that the existing reactive power allocation methods do not take into account the specific operating state of each doubly-fed induction generator (DFIG) and the established optimization model has many variables and is complicated, this paper proposes to construct an optimization model based on reactive power compensation coefficient and sensitivity factor, to reduce the number of variables in the mathematical model and simplify the expression of the relationship between each key parameter, so the speed of the reactive power and voltage control are improved. In the process of constructing specific optimization models, the objective of minimizing the active loss takes into account the operating copper consumption of each DFIG. The objective of minimizing the voltage fluctuation of each DFIG is also taken into account, in addition to the operating state constraints of each DFIG, so that the final reactive power allocation is more practical. In solving the multi-objective optimization problem, the improved NSGA-II algorithm is utilized, which can achieve the simultaneous optimization of multiple objectives, and when combined with the simplified model established in this paper, the correctness and speed of obtaining the optimal solution set of Pareto can be further improved. Finally, the effectiveness of the proposed strategy in reducing active losses and voltage fluctuations in wind farms is verified by simulation examples.

The Effect of Bearing Impedance on Online Condition Monitoring for Rotor Winding Insulation of Doubly-Fed Induction Generator

The Effect of Bearing Impedance on Online Condition Monitoring for Rotor Winding Insulation of Doubly-Fed Induction Generator

Virtual impedance control of double-fed induction generator for damping enhancement in hvdc collection system

Virtual impedance control of double-fed induction generator for damping enhancement in hvdc collection system

Sliding mode control for doubly fed induction generators system-based a wind turbine

This paper presents a contribution to the control of a Doubly-Fed Induction Generator (DFIG) integrated into a wind turbine using nonlinear control. The parameters involved in this study are the active and reactive powers exchanged between the DFIG stator and the grid. For this purpose, the modeling of the DFIG with the cascaded rectifier-inverter PWM structure was established. A numerical simulation of the DFIG, powered by the cascaded structure and controlled by the developed strategies, was performed. The simulation results show that the sliding mode control (SMC) provides a better transient response , with a shorter response time and reduced overshoot. Furthermore, it maintains good performance and stability in the presence of parameter variations such as resistance and inductance. The proposed control algorithm is also robust against parameter variations and the resulting dynamic response is fast. The simulation results confirm the validity of the mentioned advantages and the effectiveness of the proposed method. The effectiveness and robustness of the control technique were implemented and tested under MATLAB/Simulink environment.

Using the proportional dual integral strategy to improve the characteristics of the indirect field-oriented control of DFIG-based wind turbine systems

In this work, a new indirect field-oriented command (IFOC) for wind systems based on a doubly-fed induction generator (DFIG) is designed to get better energy and stream quality. Also, overcoming the problems of IFOC. It is proposed to use proportional dual integral (PDI) controllers in order to replace traditional controllers and augment the robustness of the studied wind turbine system. The proposed IFOC-PDI is a modification of the IFOC, where the basic idea behind the designed technique is to combine a proportional-integral (PI) regulator with an integral term. This technique has been applied to the machine inverter, where the IFOC-PDI aims to calculate reference voltage values. The pulse width modulation (PWM) is used to translate voltage reference values ​​into pulses to run the machine inverter. The main objective of this article is to compare the competence of the IFOC-PDI to that of the IFOC-PI in different tests, including two different wind speed profiles and DFIG parameters variation. The major benefit of this command is a decrease in harmonic distortion of the currents, and active and reactive power (Ps and Qs) fluctuations. The results using MATLAB demonstrated that the IFOC-PDI improved the IFOC-PI in the minimization of stream harmonic distortion (6.63%, 10.42%, and 17.86%) and notable minimization of fluctuations in both Ps (32.08%, 46.24%, and 12.10%) and Qs (45.95%, 66.88%, and 14.49%). Also, the overshoot value of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 57.79%, 12.41%, and 33.96%. The steady-state error of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 29.43%, 85.88%, and 76.36%. The IFOC-PDI is also very resistant in the case of DFIG parameters variation.

Backstepping control of DFIG wind turbine system based rotor flux observer

This paper introduces a novel approach to controlling a wind energy system based on a doubly fed induction generator (DFIG) using backstepping control. The proposed control method allows for independent control of the active and reactive power of the stator. Unlike traditional methods that rely on vector control of the stator fluxes and neglect the stator resistance, this approach takes into account the nonlinearities and coupled nature of the system. By using a nonlinear model in the Park frame, the control is more accurate and closer to the behavior of a real machine. This method has yet to consider any estimation of the rotor flux model. Using a high-gain observer can resolve the issue of measuring rotor flux. The stability of the nonlinear observer is demonstrated through the application of Lyapunov theory. The simulation results indicate that the suggested control scheme has enhanced the dynamic performance of the system.

Adaptive passive fault tolerant control of DFIG-based wind turbine using a self-tuning fractional integral sliding mode control

Controlling variable wind speed turbine (VWT) system based on a doubly-fed induction generator (DFIG) is a challenging task. It requires a control law that is both adaptable and robust enough to handle the complex dynamics of the closed control loop system. Sliding mode control (SMC) is a robust control technology that has shown good performance when employed as a passive fault-tolerant control for wind energy systems. To improve the closed control loop of VWT based on DFIG with the aim of improving energy efficiency, even in presence of nonlinearities and a certain range of bounded parametric uncertainties, whether electrically or mechanically, an adaptive passive fault tolerant control (AP-FTC) based on a self-tuning fractional integral sliding mode control law (ST-FISMC) developed from a novel hyperbolic fractional surface is proposed in this paper. ST-FISMC introduces a nonlinear hyperbolic function into the sliding manifold for self-tuning adaptation of control law, while fractional integral of the control law smooths discontinuous sign function to reduce chattering. Additionally, this work introduces an adaptive observer, developed and proved based on a chosen Lyapunov function. This observer is designed to estimate variations in electrical parameters and stator flux, ensuring sensorless decoupling in indirect field- oriented control (SI-FOC) of DFIG. Lyapunov theory is also used to prove stability of states vectors in closed control loop with presence of bounded parameters uncertainties or external disturbances. Simulation results show that the proposed approach offers better performance in capturing optimal wind energy, as well as the ability to regulate active/reactive power and high resilience in presence of occurring parameter uncertainties or external disturbances.

Integrating Bayesian inference and neural ODEs for microgrids dynamics parameters estimation

The integration of solar and wind energy sources in microgrids has witnessed significant growth, giving rise to distinct challenges due to their intermittent nature when it comes to achieving efficient microgrid control. However, estimating the parameters of the dynamic microgrid components facilitates capturing the complex and time-varying characteristics of renewable energy generation. This requires an accurate estimation of the parameters from the dynamic differential equations for effective modeling and control. In this research paper, we presented a novel methodology based on the integration of Bayesian inference and Neural ODEs. The Bayesian inference quantifies the uncertainty, and the Neural ODEs model the dynamic systems. By combining the strengths of both methods, we aimed to achieve a precise and robust parameter estimation of the dynamic microgrid components. The methodology is validated on a simulated microgrid that consists of a diesel generator, Solar PV array, double-fed induction generator, and a battery energy storage system. The results showed promised inferences estimation obtained from the parameter posterior distribution even in the presence of uncertainty. This can enhance our understanding of the dynamics of renewable energy systems and can contribute to the advancement of decision-making microgrid control strategies.

Optimization of Fuzzy Control Parameters for Wind Farms and Battery Energy Storage Systems Based on an Enhanced Artificial Bee Colony Algorithm under Multi-Source Sensor Data.

With the rapid development of sensors and other devices, precise control for the generation of new energy, especially in the context of highly stochastic wind power generation, has been strongly supported. However, large-scale wind farm grid connection can cause the power system to enter a low inertia state, leading to frequency instability. Battery energy storage systems (BESSs) have the advantages of a fast response speed and high flexibility, and can be applied to wind farm systems to improve the frequency fluctuation problem in the process of grid connection. To address the frequency fluctuation problem caused by the parameter error of the fuzzy membership function in the fuzzy control of a doubly fed induction generator (DFIG) and a BESS, this paper proposes an improved Artificial Bee Colony (ABC) algorithm based on multi-source sensor data for optimizing the fuzzy controller to improve the frequency control ability of BESSs and DFIGs. A Gaussian wandering mechanism was introduced to improve the ABC algorithm and enhance the convergence speed of the algorithm, and the improved ABC algorithm was optimized for the selection of fuzzy control affiliation function parameters to improve the frequency response performance. The effectiveness of the proposed control strategy was verified on the MATLAB/Simulink simulation platform. After optimization using the proposed control strategy, the oscillation amplitude was reduced by 0.15 Hz, the precision was increased by 40%, and the steady-state frequency deviation was reduced by 26%. The results show that the method proposed in this paper provides a great improvement in the frequency stability of coordinated systems of wind farms and BESSs.

A review of single stage and multistage power converters for doubly fed induction generator integrated with power grid

The doubly fed induction generator (DFIG) is the most popular induction generator for onshore wind energy conversion system (WECS). Therefore, the purpose of research is to optimize power transfer from DFIG to power grid which requires frequency and voltage stability in power converters. Hence, the single-stage and multistage power converter topologies associated with grid-integrated DFIG are thoroughly examined in this work. In the single stage, a matrix converter and cycloconverter are used. Whereas, the multistage topologies include two-level back-to-back (2L-B2B) converter, Z-source converter, and multilevel converters. Furthermore, three-level neutral point clamped (3L-NPC) voltage source converters with battery energy storage systems (BESS) and modified superconducting fractional order terminal sliding mode controllers (MSTFOTSMC) have been used with multilevel converter both at rotor side converter (RSC) and grid side converter (GSC) for stabilized generated voltage and higher power output. The MATLAB simulation results demonstrate that the system effectively controls fluctuations in voltage and current thereby improving the power quality in unbalanced situations.

FRT Capability Enhancement of DFIG-based Wind Turbine with Coordination Control of MSVC and FCL

Objective: To address the problems of various FRT (fault ride through) schemes in DFIG (doubly fed induction generator) systems, especially their applicability under different voltage sags, a combination scheme of an MSVC (minimized series voltage compensator) and FCL (fault current limiter) is proposed. Methods: Based on the analysis of the mathematical model of the DFIG and considering the capacity and volume in the process of practical engineering, the application structure and specific control strategy of an MSVC in DFIG systems are designed on the stator side, and the application effect is analyzed theoretically. Simultaneously, the application structure and control strategy of the FCL is proposed on the rotor side, and the application effect of the combination scheme is theoretically deduced and analyzed. Moreover, the simulation model is built on the MATLAB/Simulink platform. Results: The simulation results show that the scheme can quickly and effectively recover the fault voltage of the DFIG under different voltage sag degrees and has better dynamic performance. At the same time, it can effectively limit the fault current and suppress the DC-link voltage of the rotor side, and the transition process is relatively stable. Conclusion: The purpose of improving the FRT capability of the DFIG system is realized.

Robust hybrid control strategy for active power management in Kabertene wind farm within Algeria’s PIAT grid

The paper introduces a hybrid control strategy for optimised active power management in Algeria's Kabertene wind farm, crucial for the pole insalah-adrar-timimoune (PIAT) grid's stability. This strategy merges simultaneous interconnection and damping assignment (SIDA) passivity theory, passivity-based control (PBC), and multivariable proportional-integral-derivative (PID) controllers. This combined approach ensures frequency and voltage stability within the PIAT grid, which encompasses various elements like wind farms, solar plants, gas turbines, and dynamic impedance (Z), current (I), and active power (P) (D-ZIP), load model. By tailoring controllers for doubly fed induction generators (DFIGs) using SIDA-PBC principles and optimising internal parameters, the strategy achieves precise control of active power output. Additionally, particle swarm optimisation (PSO) refines power scheduling, which is especially beneficial for intermittent renewable sources like DFIGs. This comprehensive strategy offers numerous advantages: improved network stability, minimized voltage deviations, reduced frequency fluctuations, and enhanced integration of renewable energy sources. The paper emphasises practical implementation considerations, providing valuable guidance for efficient Kabertene wind farm operation and integration. This research contributes significantly to fostering cleaner and more reliable energy systems, facilitating the PIAT grid's transition towards sustainable energy generation.

Small signal stability analysis of a wind power system integrated with a multi-band supplementary damping controller

Abstract With the integration of wind turbines represented by doubly-fed induction generators (DFIG) into the power system, the inertia level of the system decreases sharply, and small disturbances can easily cause low-frequency oscillation (LFO) in the system. In this paper, we propose a multi-band supplementary damping controller (MBSDC) directly applied to the active power control link of the rotor-side converter in the wind power generation system. We establish a linearized model for DFIG integrated with the power system, calculate eigenvalues, and screen out multiple electromechanical oscillation modes to be suppressed. Based on the calculation results, an MBSDC is designed to suppress LFO, and we propose a parameter-setting algorithm to enhance the suppression effect. Taking the New England 10-generator 39-bus system containing DFIG as an example for simulation verification, the results show that the MBSDC and parameter setting algorithm designed in this paper can effectively suppress LFO.

Enhancement of frequency transient response using fuzzy-PID controller considering high penetration of doubly fed induction generators

In modern power systems, renewable-based power plant such as wind power system is integrated significantly. Among numerous types of wind power systems doubly fed induction generators (DFIG) is becoming favorable in the last few years. However, adding a wind power plant could give a new challenge to the power system, especially in frequency stability. Hence, it is important to control the frequency of the power system to be able to find its initial condition in every condition. Generally, the frequency of the power system can be controlled by using automatic generation control (AGC). AGC is used to maintain the balance between generating capacity and the load by adding integral control to the governor. However, with more and more wind power systems in the grid conventional AGC is unsuitable. Hence, it is important to have an advanced AGC based on the artificial intelligence method. This paper proposed the application of fuzzy-proportional integrator derivative (fuzzy-PID) for AGC in power systems considering the high penetration of wind power systems. From the simulation results, it is found that the proposed method can reduce the overshoot and accelerate the settling time of frequency better than using conventional AGC.

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

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

Performance of Robust Type-2 Fuzzy Sliding Mode Control Compared to Various Conventional Controls of Doubly-Fed Induction Generator for Wind Power Conversion Systems

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.