Induction Generator Based Wind Turbine Research Articles

An Improved Strategy of Grid-Forming DFIG Based on Disturbance Rejection Stator Flux Control

Grid-forming (GFM) control are promising for doubly fed induction generator-based wind turbines (DFIG -Based WTs) due to its grid-support ability and stable operation when connected to weak grid. However, GFM-DFIG might suffer from instability under symmetrical grid fault, if its electromagnetic and synchronous dynamics are poor. Therefore, an improved strategy of GFM-DFIG based on disturbance rejection stator flux control (DRSFC) is proposed in this paper. The DRSFC consists of a PI-based rotor-current loop and an active disturbance rejection control (ADRC)-based stator-flux outer loop, and both the better electromagnetic performance and the steady-state voltage source operation are achieved. Besides, impacts of DRSFC on GFM-DFIG are exposed via small-signal and large-signal analysis, and the potential inertia in the inner control loops is revealed. It is suggested that this potential inertia is reshaped by DRSFC, so the impact of inner control loop on the synchronization of GFM-DFIG can be quantitatively studied and controlled. On this basis, a pair of asymmetrical compensation are designed to improve its electromagnetic decay and synchronous dynamic. Finally, experiments are carried out to verify the effectiveness of proposed strategy.

Enhanced Control of Doubly Fed Induction Generator Based Wind Turbine System Using Fractional-Order Fuzzy PD+I Regulator

Enhanced Control of Doubly Fed Induction Generator Based Wind Turbine System Using Fractional-Order Fuzzy PD+I Regulator

A robust damping control for battery energy storage integrated power systems to mitigate inter-area oscillations

This paper presents the effect of a Battery Energy Storage System (BESS) on the power system inter-area oscillations under changing load conditions. The dynamic interaction between the BESS control modes and synchronous generators, along with BESS control parameters, influence the damping of prominent inter-area oscillations under different loading conditions. Furthermore, H∞ mixed sensitivity scheme-based Wide-Area Damping Controller (WADC) is proposed for BESS. This controller is designed using the Linear Matrix Inequality (LMI) framework to mitigate the prominent inter-area oscillation of the power system. Sensitivity to control parameter variation and the geometric measure of the observability are utilized to select the location and feedback signal for the WADC. The performance of the proposed WADC is compared with an Energy Storage System-based stabilizer and WADC proposed in an existing work on a modified New England ten-machine benchmark system. The Real-Time Digital Simulator (RTDS) platform is used to assess the real-time viability of the proposed WADC. The simulation results demonstrate that the proposed WADC can effectively diminish several inter-area modes. Additionally, it offers robust performance under varying load conditions, contingencies and with communication delays in feedback signals. The proposed controller is also effective under the system integrated with Doubly Fed Induction Generator-based Wind Turbine System.

Control of Self-Excited Induction generator based wind turbine using by IM controller

Control of Self-Excited Induction generator based wind turbine using by IM controller

Protection of Doubly Fed Induction Generator-Based Wind Turbines Against Loss of Excitation of the Rotor Winding

Protection of Doubly Fed Induction Generator-Based Wind Turbines Against Loss of Excitation of the Rotor Winding

Supervisory control of reactive power in wind farms with doubly fed induction generator-based wind turbines for voltage regulation and power losses reduction

This paper proposes a strategy based on the secondary voltage control (SVC) and the use of grid codes recommended by the system operator to determine the reactive power reference value between a wind farm (WF) with doubly-fed induction generator (DFIG) and the electrical grid. The proposed strategy seeks to determine the reactive power reference value required of WF during normal operating and grid faults. When the voltage deviation is within the normal range, the proposed strategy maintains a unity power factor (UPF). If the voltage deviation exceeds the normal range, it provides reactive power compensation to ensure voltage stability. To achieve this objective, the proposed strategy is compared with the SVC. This strategy can reduce the size of potential compensation devices, such as static synchronous compensators, to be used to improve the WF response, if needed. The participation of the grid converter side (GSC) in the reactive power control allows the DFIG to reduce power losses and increases the life of the converters, especially the rotor converter side (RSC). The strategy proposed in this work is implemented on Matlab/Simulink using the S-Function builder to evaluate their performance, which facilitates its integration into real control boards and testing in real experiments in the future.

Enhancing power control in doubly fed induction generator based wind turbines: a performance comparison of fuzzy logic and sliding mode control methods

Abstract Effective power regulation is critical for ensuring the stability and performance of Doubly Fed Induction Generator (DFIG)-based wind turbines. This study conducts a comparative study between two control methodologies: fuzzy logic control (FLC) and sliding mode control (SMC), to regulate power in DFIG-based wind turbines. The paper emphasizes the importance of power regulation in wind turbines and its impact on grid stability, presents mathematical equations governing DFIG-based wind turbine systems, encompassing machine equations, power equations, and control objectives related to power regulation. A comprehensive model of the DFIG-based wind turbine system is developed, accounting for dynamic machine behavior and grid interface considerations. The modeli ng process integrates relevant electrical and mechanical components, along with power regulation control strategies. Subsequently, FLC and SMC control methodologies are developed and implemented to regulate desired power. Detailed discussions on controller design and tuning are provided, aligning with specific power control requirements. The results highlight SMC’s effectiveness in achieving precise power regulation within DFIG-based wind turbines, showcasing its superior response characteristics. The study offers valuable insights into the advantages and trade-offs associated with each control approach, aiding researchers and practitioners in selecting the most suitable control methodology for their operational needs. In summary, this paper contributes to the field of wind turbine control systems through a comparative study of FLC and SMC controllers, focusing on regulating power in DFIG-based wind turbines. The findings demonstrate SMC’s superior performance in response, enhancing our understanding of control methodologies for optimizing wind turbine performance and grid integration in sustainable energy systems.

Adaptive fractional backstepping intelligent controller for maximum power extraction of a wind turbine system

Controlling wind power plants is a challenging issue, however. This is due to its highly nonlinear dynamics, unknown disturbances, parameter uncertainties, and quick variations in the wind speed profiles. So robust controllers are needed to overcome these challenges. This paper suggests two novel control approaches for doubly fed induction generator-based wind turbines. Its key objective is to regulate the generator speed and rotor currents. A radial basis function (RBF) neural network disturbance observer based fractional order backstepping sliding mode control (SMC) is presented to control the rotor currents. This RBF neural network-based disturbance observer estimates unknown disturbances. Also, a new adaptive fractional order terminal SMC is suggested for the control of the generator speed. This robust chattering-free controller that does not require any information about the bound of uncertainties fractional calculus is adopted in the SMC design to eliminate undesired chattering phenomena. The controller parameters are optimally tuned utilizing the ant colony optimization algorithm. The proposed approach was validated using a simulation study entailing various conditions. Its performance was also compared to that of the conventional backstepping and conventional backstepping sliding mode controller. The simulations results verified the approach's ability to maximize power extraction from the wind and properly regulate the rotor currents. The proposed method has about 20% less tracking error than the other two methods, which means 20% higher efficiency.

Control of self-excited induction generator based wind turbine using current and voltage control approaches

The self-excited induction generator (SEIG) is widely applied in the wind energy conversion system (WECS) to enhance power generation. The power generation from WECS is varied in terms of varying wind speed. Hence, to improve the working of SEIG-based WECS, the multi-stage coati optimized proportional integral (CPI) fractional order proportional integral derivative (FOPID) controller is proposed in this work. The proposed coati optimized proportional integral - fractional order proportional integral derivative controls the SEIG’s grid side converter and generator side converter. The coati optimization algorithm optimizes the controller parameters of a proposed multi-state controller. The proposed CPI-FOPID controls both the voltage at the grid side converter and the current at a generator side converter. Moreover, the pitch angle of the wind turbine (WT) is controlled by the fuzzy-based tilt integral derivative (F-TID) controller. The proposed work will be implemented on the Matlab/Simulink platform, and the THD of 0.63% has proven the efficacy of the proposed methodology.

Fixed-time fuzzy adaptive control scheme for doubly fed induction generator–based wind turbine

This work focuses on the issue of designing a fixed-time fuzzy adaptive controller for variable-speed doubly fed induction generator-based wind turbine. The main goal is to optimize the wind turbine power production, while improving the performance of the overall control system such as, convergence speed, tracking accuracy, and robustness. For the control design, the backstepping technique is adopted, and fuzzy adaptive systems are employed as universal approximators to estimate continuous functional uncertainties. Using fixed–time stability concept, a detailed mathematical stability proof of the closed-loop control system is performed. Simulation results are presented to testify the efficiency of the designed control approach.

Comparative Study of Robust RSC Control of Doubly Fed Induction Generator Based Wind Turbine under Grid Frequency and Voltage Variations

The configuration of a grid-connected doubly fed induction generator (DFIG) for wind energy generation systems consists of direct coupling of the generator stator windings with the grid and partial coupling of the rotor through power converters. This structure makes the system sensitive to the fault grid. Thus, robust control techniques are required to deal with the undesirable transient sequences in the network. In this paper, two robust controllers have integrated to regulate the stator active and reactive power of DFIG based wind turbine. Then, they have been tested and compared to verify their performances when abnormal grid networks have occurred. Firstly, we used high order sliding mode (HOSM) based Super Twisting, which keeps the same conventional sliding mode performances, such as fast dynamic response and redundancy to the extern disturbances, with a simple design and chattering reduction. Secondly, we implement the backstepping control approach which is known for its robustness in transient sequences. A number of simulations have carried out to evaluate the ride-through performance of both control strategies in case of low grid voltage dips and grid frequency variations.

Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization

This work proposes a parallel multi-layer Monte Carlo optimization algorithm (PMMCOA) that optimizes proportional–integral parameters for a doubly fed induction generator-based wind turbine controller. The PMMCOA, an improved form of the Monte Carlo algorithm, realizes the optimization process via a parallel multi-layer structure. The PMMCOA includes rough search layers, precise search layers, and re-precise search layers. Each layer of the PMMCOA adopts a multi-region and multi-granularity approach to increase the diversity and randomness of the search samples. The PMMCOA is employed to tune the controller parameters for achieving maximum power point tracking and improving generation efficiency. The controller fitness function reflects the sum of the rotor angular velocity error and the reactive power error. Compared with the five metaheuristic algorithms, the PMMCOA has a higher global convergence and more accurate power tracking ability.

Condition monitoring through DWT-PSD-FLS approach of faulty wind generators

This work investigates the prospect of rotor broken bar defect diagnosis in squirrel cage induction generator-based wind turbine using fuzzy logic system (FLS) of the stator currents. The generator current signal is analyzed through the power spectral density (PSD) to diagnose the magnitudes and frequencies associated with various defects. These magnitudes and frequency components are used to apply the system of Fuzzy logic by simulation software.

Limits of reactive power compensation of a doubly fed induction generator based wind turbine system

The doubly fed induction generator (DFIG) systems feature a significant amount of free power capacity that may be used for reactive power adjustment when they are put into practical use. This change, which is occasionally overlooked, is a significant one. Using DFIG systems for wind turbines (WT), this paper explored strategies for reducing and using reactive power. In order to investigate the power characteristic and how it is regulated in DFIG systems, a mathematical model for the steady-state performance of DFIG WT has been developed and presented. Here is a detailed derivation of the limiting range of DFIG's reactive power capacity as well as the physical constraints on reactive power output. The distribution of the DFIG WT at a distribution network's end is demonstrated by a simulation example. Within this simulation, reactive power management strategy, load fluctuation, and the change in wind speed are all taken into consideration. Due to the possibility of a rise in the voltage at the access point, can concluded that both acceptable and efficient to use DFIG WT's reactive power capabilities as an additional continuous reactive power source for effectiveness.

Integrated Assessment of the Reliability and Frequency Deviation Risks in Power Systems Considering the Frequency Regulation of DFIG-Based Wind Turbines

Recently, frequency regulation strategies have been widely adopted in the operation and control of doubly fed induction generator-based wind turbines (DFIG-WTs). Thus, wind power, which is becoming an increasingly important energy source, is expected to play a significant role in both power generation and frequency regulation in modern power systems. Under such circumstances, maintaining the reliability and frequency of power systems at a designated level may be more challenging due to inherent uncertainties in wind power generation. In this paper, the integrated assessment of the reliability and frequency deviation risks of power systems with a high penetration level of wind power is investigated. A multi-time scale analytical framework is proposed to calculate the integrated reliability and frequency deviation indices. The coupling between the reliability and frequency deviation is further addressed by developing a novel frequency-sensitive reliability model of the electric generator. Frequency deviations under supply/demand fluctuations and device failures are analyzed, and the power system frequency regulation process is modeled with the fuzzy adaptive virtual inertial response of DFIG-WTs and energy storage system (ESS). Furthermore, IEEE-RTS79 is used to verify the validity of the proposed model and solution method.

Reduced Order DFIG Models for PLL-Based Grid Synchronization Stability Assessment

This paper presents a reduced-order modeling approach to study the grid synchronization stability of type-3 wind turbine generator (WTG) by considering the dynamics of the phase-locked loop (PLL) alone. The proposed model is validated by comparing its time-domain response and small-signal results with the full-order dynamical model of a type-3 WTG system. Extension of the proposed reduced-order model is shown in a wind farm with N numbers of the WTGs, and time-domain simulations are performed under stable and unstable scenarios. The developed model is further utilized for directly assessing the transient stability of a doubly-fed induction generator-based wind turbine generator (DFIG-WTG) system leveraging Lyapunov's direct method. From the direct transient stability assessment methodology, an approximate estimate of the critical clearing time (CCT) is obtained for the DFIG-WTG system to ensure large-signal stability following severe grid fault. Finally, the parametric conditions are derived theoretically, which can determine the stable and unstable region of operation of the DFIG-WTG system with respect to the PLL parameters, grid impedance, and input wind speed.

Multi-objective high-dimensional multi-fractional-order optimization algorithm for multi-objective high-dimensional multi-fractional-order optimization controller parameters of doubly-fed induction generator-based wind turbines

Aiming at the operation control of doubly-fed induction generator-wind energy systems, this study firstly introduces multi-dimensional information feedback and fractional-order theory and designs a high-dimensional multi-fractional-order controller in the rotor side converter. Secondly, for the tuning optimization of controller parameters of doubly-fed induction generators, this study proposes a high-dimensional multi-fractional-order optimization. Finally, this study proposes a multi-objective high-dimensional multi-fractional-order optimization algorithm for the multi-objective optimization problems of control parameters tuning and optimization. This study adopts an adaptive grid strategy to update non-dominated solutions for external archives with crowded conditions. Furthermore, this study adopts a roulette strategy to select the optimal global position in the iterative process. This study utilizes multi-objective test functions to verify the effectiveness of the proposed multi-objective optimization. The Pareto optimal solutions and five types of statistical data from two indexes show that the proposed multi-objective optimization has improved convergence, diversity, and operational stability. Compared with five algorithms, the proposed multi-objective optimization can obtain Pareto optimal solutions with uniform distribution and good diversity in the multi-objective tuning of control parameters of the designed multi-objective controllers for doubly-fed induction generators. Therefore, decision-makers can choose the control parameters according to the actual needs. The test results show that the designed multi-objective controller optimized by the proposed multi-objective optimization has more accurate power tracking ability and superior control performance.

Theoretical analysis for low voltage ride through capability in doubly-fed induction generator-based wind turbines with stator resistive hardware model

Theoretical analysis for low voltage ride through capability in doubly-fed induction generator-based wind turbines with stator resistive hardware model

Nonlinear Stochastic Adaptive Control for DFIG-Based Wind Generation System

The aim of this paper is to extract the maximum power from wind energy for the doubly fed induction generator based wind turbine system (DFIG-WT) under the continuous stochastic perturbations of wind speed. The DFIG-WT is modeled as the Itô stochastic differential equations. The stochastic backstepping control method and the gain suppressing inequality technique are employed to guarantee that the relative rotor speed to the optimal value is bounded in probability. Furthermore, we extend the bounded result to the asymptotic stability of the rotor speed control loop. In addition, the parametric uncertainties in DFIG-WT are also considered in our control synthesis. The simplicity, robustness and efficiency of the designed controller are verified under the special wind speed with white noise by the numerical simulation of a 660 KW DFIG-WT.

Analysis of Doubly Fed Induction Generator-based wind turbine system for fault ride through capability investigations

A Doubly Fed Induction Generator has a stator winding directly coupled with grid whereas rotor is to the grid via a fault-prone converter. In early times, when a fault occurred, these generators were required to disengage from the grid. However, due to the increased penetration, grid operators demanded WTs remain connected to the grid. Thus, this paperwork integrates crowbar protection with a Battery Energy Storage System (BESS) to improve Fault Ride Through (FRT) capability. For performance evaluation under transient conditions, a three-phase symmetrical fault is imposed at a time of 2 seconds. By using the suggested technique, the DC-link voltage is observed to improve and remain at 1150 V with minor fluctuation. Likewise, the stator and rotor currents are observed to remain at their nominal value after 2.15 seconds. MATLAB-Simulink software is used for modeling and simulation by obtaining all the system’s actual parameters from ADAMA-II Wind Farm.