Doubly-fed Induction Generator (dfig)

İndiksiyon ve iki beslemeli indiksiyon generatörleri rüzgar gücü sistemlerinde elektrik üretimi için yaygın olarak kullanılır. İndiksiyon generatörlerin ve iki beslemeli indiksiyon generatörlerin tanımları rüzgar enerji sistemleri için bu çalışmada verilmiştir. Farklı bağlantı tipleri ve koşulları iki farklı rüzgar jeneratörü için şebeke ve rüzgar türbinleri için bu çalışmada incelenmiştir. Bir rüzgar çiftliği modeli indiksiyon generatörü ve iki beslemeli indiksiyon generatörü için MATLAB/Simulink de modellenmiştir. İlk olarak simulasyon sonuçları normal çalışma koşulları için sunulmuş ve tartışılmıştır. İkinci olarak ise rüzgar çiftliği modeli hata durumları için simule edilmiştir. Farklı hata koşulları altındakı bu IG ve DFIG sonuçları statik kompanzatörün bir fonksiyonu olarak verilmiş ve tartışılmıştır. Bu sistemin üstünlük ve dezavantajları verilmiş ve değerlendirilmiştir. https://dx. Induction and doubly-fed induction generators are widely used in wind power systems for electricity generation. Description of induction generator (IG) and doubly-fed induction generator (DFIG) for wind power generation systems are given in this paper. Different connection types and conditions for two different types of wind generators with the grids and wind turbines are investigated in this study. A wind farm model is simulated using an induction generator and a doubly-fed induction generator in MATLAB/Simulink. The simulation results under normal operating conditions are presented and discussed firstly. Wind farm models are simulated under fault conditions secondly. The results of the IG and DFIG system under various fault conditions as a function of static compensator (STATCOM) are presented and discussed. The superiority and disadvantages of this system are given and evaluated. https://dx.

This paper presents the performance analysis of Fuzzy Logic Controller through unbalanced voltage with the controlled output of doubly-fed induction generator produced by wind energy conversion system. A fuzzy logic controller is designed using MATLAB/Simulink, for the control strategy of rotor side converter (RSC) and grid side converter (GSC) is so that, the torque and dc voltage are remain stable during unbalanced loading. The machine uses two back to back converter controllers, to overcome problem due to harmonics used with various control schemes. Moreover, a THD analysis confirms the best quality of grid injected power.

This research presents a new scheme to extract the maximal available power from a wind turbine employing a doubly fed induction generator (DFIG). This scheme is developed from the wind turbine's MPPT-curve. Furthermore, we propose control laws for the rotor and grid side-converters. The stability of the proposed maximum available power method and the control laws are proved mathematically upon Lyapunov's stability criterion. Their efficiency is tested through the simulations of a DFIG wind turbine in Matlab/Simulink. Simulation results are analyzed and compared with that using a conventional scheme. Thanks to the suggested scheme, the wind turbine can track its maximum power point better and the electric energy output is higher comparing with that using the conventional scheme. Furthermore, by the suggested controllers, the rotor speed and current of the DFIG converged to their desired values. In other words, the wind turbine can achieve stable operations by the suggested control laws. Chieu district, Danang city, Vietnam 84-988983127 pdchung@dut.udn.vn 1. INTRODUCTION The maximum power generation of a wind turbine has been interested in several decades and many algorithms have been suggested. According to [1], previous maximum power point tracking (MPPT) methods can be listed into three groups including indirect power controller, direct power controller, and others. The indirect power controller which aims to maximize mechanical power by using tip-speed ratio [2], [3], optimal torque [4], and power signal feedback MPPT algorithm [5] is simplicity and only allows the wind turbine to track its MPPT-curve quickly when a wind speed measurement is precise and instantaneous. In the case of an unavailable wind measurement, a wind turbine using the indirect power controller fails to track its maximum power point quickly and accurately [6], [7]. The direct power controller which maximizes electric power by using the perturbation and observation (P&O) algorithm such as: Hill climb search [8], incremental conductance [9], optimal-relation based MPPT algorithm [10], [11], and hybrid MPPT algorithm [12] does not require any wind turbine knowledge and available anemometer. Unfortunately , a wind turbine using the direct power controller cannot track its maximum power because this controller cannot recognize instantaneously the variation in wind speed. Until now, this controller has been implemented to adjust the voltage and current of DC circuit in a permanent magnetic synchronous generator wind turbine. The last group is developed based on soft computing techniques like Fuzzy [13] and Neural network [14]. A wind turbine using these methods only has a good performance when the full information of the wind turbine is available. However, these methods are complexity and large memory requirement. Hence, a new MPPT scheme for DFIG wind turbines should be researched. To control the generator-wind turbine, proportional-integral (PI) control is normally implemented because of its simplicity [7], [15], [16]. However, by using the PI control, we cannot guarantee the wind turbine system will become stable operation [17], [18]. Recently, control laws based on sliding mode were suggested for rotor speed adjustment [19], [20]. However, these control laws require an available wind speed measurement. Hence, we need

Reliable load frequency control (LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC) based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints (GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints.

Doubly-fed Induction Generator (DFIG) is the most common rotatory machine which is used on the grid connected wind energy conversion system for the fulfillment of the system requirement such as grid stability, fault ride through (FRT), power quality improvement, and grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine rather the control strategy is used in both the stator as well as rotor side along with converters to fulfill the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary. The machine uses two back-to-back converters. The grid side converter is modeled to control the active and reactive power independently along with dc-link voltage. The machine side converter is modeled to control the reactive power of the machine and maintain the speed constant irrespective of the transient behavior of the grid. In this paper the performance of the DFIG system is analyzed under grid voltage fluctuation and the theoretical results are obtained from the MATLAB/ SIMULINK environment. The proposed work is also validated experimentally using RT-LAB.

The main objective of Automatic Generation Control (AGC) is to keep the frequency within specified limits through primary and secondary control. In this study, a model of two area thermal non-reheat power system with integration of Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion (WEC) into both areas is presented. A Proportional Integral Derivative (PID) controller and a Fuzzy Logic Controller (FLC) have been applied and compared. The Proposed controllers are used to improve the dynamic response as well as to reduce or eliminate the steady-state error in Area Control Error (ACE). FLC has been offered better and faster performance over the PID controller. The results obtained prove the impact of DFIG-based WEC on AGC and confirm the participation of the DFIG in the frequency system.

A doubly-fed induction generator (DFIG) is highly vulnerable to the grid faults that induce large electromotive force in its rotor circuit. Large penetration of DFIG-based wind energy conversion systems (WECS) into existing power systems raises the importance of low-voltage ride-through (LVRT) capability of the DFIG. Motivated by the above arguments, this study focuses on the mitigation of DC-link voltage variations with the help of a crowbar based on an energy storage device that supports the DFIG to enhance its LVRT capability during grid faults. The proposed design is incorporated into a combination of a rotor-side crowbar to limit the rotor over-currents. Moreover, an efficient synchronization mechanism is also proposed for smooth connection of a DFIG with the grid to minimize the startup inrush currents. The overall proposed schemes are intended for a 1.5 MW DFIG-based WECS. Extensive simulations are carried out in Simulink/Matlab to validate the performances of the proposed schemes. The results confirm that the proposed control schemes are capable to cope with DC-link voltage variations and rotor over-currents within safe operating limits and the smooth connection of a DFIG with the grid as well without significant inrush currents.

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

This paper presents the complete modeling and simulation of Wave Energy Conversion System (WECS) driven doubly-fed induction generator with a closed-loop vector control system. Two Pulse Width Modulated voltage source (PWM) converters for both rotor-and stator-side converters have been connected back to back between the rotor terminals and utility grid via common dc link. The closed-loop vector control system is normally controlled by a set of PID controllers which have an important influence on the system dynamic performance. This paper presents a Multi-objective optimal PID controller design of a doubly-fed induction generator (DFIG) wave energy system connected to the electrical grid using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). PSO and GA are used to optimize the controller parameters of both the rotor and grid-side converters to improve the transient operation of the DFIG wave energy system under a fault condition as compared with the conventional methods to design PID controllers.

In this paper, descending viewer method (DVM) projected for finding and fault tolerant control of stator inter-turn short circuit faults in doubly-fed induction generators based in wind turbine. A process has been developed that allows the way from ostensible controllers designed for strong condition, to vigorous controllers designed for defective condition. Finally value of the rotor resistance estimated & is based on the use of the error between real and probable value of doubly fed induction generator (DFIG) in faulty condition, this will perk up the performance of this viewer. Simulation results show the reliability of the proposed DVM approach.