Showing 7 results for Doubly Fed Induction Generator
M. J. Abbasi, H. Yaghobi,
Volume 12, Issue 4 (12-2016)
Abstract
The doubly fed induction generator (DFIG) is one of the most popular technologies used in wind power systems. With the growing use of DFIGs and increasing power system dependence on them in recent years, protecting of these generators against internal faults is more considered. Loss of excitation (LOE) event is among the most frequent failures in electric generators. However, LOE detection studies heretofore were usually confined to synchronous generators. Common LOE detection methods are based on impedance trajectory which makes the system slow and also prone to interpret a stable power swing (SPS) as a LOE fault. This paper suggests a new method to detect the LOE based on the measured variables from the DFIG terminal. In this combined method for LOE detection, the rate of change of both the terminal voltage and the output reactive power are utilized and for SPS detection, the fast Fourier transform (FFT) analysis of the output instantaneous active power has been used. The performance of the proposed method was evaluated using Matlab/Simulink interface for various power capacities and operating conditions. The results proved the method's quickness, simplicity and security.
R. Pour Ebrahim, S. Tohidi, A. Younesi,
Volume 14, Issue 1 (3-2018)
Abstract
In this paper, a new sensorless model reference adaptive method is used for direct control of active and reactive power of the doubly fed induction generator (DFIG). In order to estimate the rotor speed, a high frequency signal injection scheme is implemented. In this study, to improve the accuracy of speed estimation, two methods are suggested. First, the coefficients of proportional-integral (PI) blocks are optimized by using Krill Herd algorithm. In the second method, the fuzzy logic control method is applied in the estimator structure instead of PI controllers. The simulation results for the proposed methods illustrate that the estimated speed perfectly matches the actual speed of the DFIG. In addition, the desired slip value is achieved due to the accurate response. On the other hand, the active and reactive power responses have fast dynamics and relatively low oscillations. Moreover, the fuzzy controller shows more robustness against the variations of machine parameters.
S. Chikha,
Volume 14, Issue 3 (9-2018)
Abstract
In this paper we propose a new configuration of the wind farm connecting with an electrical grid. The proposed Wind Energy Conversion System (WECS) is based on a two stages six-leg matrix converter using to drive a two Doubly Fed Induction Machines operating at different wind speeds. Each Doubly Fed Induction Generator (DFIG) is controlled through the rotor currents using the Finite Set Model Predictive Model (FS-MBC). The proposed control method selects the optimal switching state of the converter that minimizes the cost function where it represents the desired behavior of the system. The optimal voltage vector is then applied to the output of the power converter. The most advantage of the proposed control is its simplicity in implementation, since the method avoids the use of any linear or nonlinear controllers except for the external speed loop and there is no need for any type of modulator such as in PWM or SVM modulation. A cost function is formulated according to desired performance such as regulation of the stator active and reactive powers of the DFIGs and reactive power in the filter side. The control algorithm selects and applies the optimal voltage vector to the DFIG rotor terminals. The supervision algorithm distributes the active and reactive power references in proportional way for each wind turbines. From a safety point, this algorithm provides each wind turbines still operate far from its limits. The performance of a six leg IMC in WECS chain is evaluated in term of a good tracking performance.
H. Benbouhenni, Z. Boudjema, A. Belaidi,
Volume 14, Issue 4 (12-2018)
Abstract
This paper applied second order sliding mode control (SOSMC) strategy using artificial neural network (ANN) on the rotor side converter of a 1.5 MW doubly fed induction generator (DFIG) integrated in a wind turbine system. In this work, the converter is controlled by a neural space vector modulation (NSVM) technique in order to reduce powers ripples and total harmonic distortion (THD) of stator current. The validity of the proposed control technique applied on the DFIG is verified by Matlab/Simulink. The active power, reactive power, torque and stator current are determined and compared with conventional control method. Simulation results presented in this paper shown that the proposed control scheme reduces the THD value and powers ripples compared to traditional control under various operating conditions.
H. Benbouhenni,
Volume 15, Issue 3 (9-2019)
Abstract
This article presents a sliding mode control (SMC) with artificial neural network (ANN) regulator for the doubly fed induction generator (DFIG) using two-level neural pulse width modulation (NPWM) technique. The proposed control scheme of the DFIG-based wind turbine system (WTS) combines the advantages of SMC control and ANN regulator. The reaching conditions, robustness and stability of the system with the proposed control are guaranteed. The SMC method which is insensitive to uncertainties, including parameter variations and external disturbances in the whole control process. Finally, the SMC control with neural network regulator (NSMC) is used to control the stator reactive and a stator active power of a DFIG supplied by the NPWM strategy and confirms the validity of the proposed approach. Results of simulations containing tests of robustness and tracking tests are presented.
Z. Rafiee, M. Rafiee, M. R. Aghamohammadi,
Volume 16, Issue 3 (9-2020)
Abstract
Improving transient voltage stability is one of the most important issues that must be provided by doubly fed induction generator (DFIG)-based wind farms (WFs) according to the grid code requirement. This paper proposes adjusted DC-link chopper based passive voltage compensator and modified transient voltage controller (MTVC) based active voltage compensator for improving transient voltage stability. MTVC is a controller-based approach, in which by following a voltage dip (VD) condition, the voltage stability for the WF can be improved. In this approach, a voltage dip index (VDI) is proposed to activate/deactivate the control strategy, in which, two threshold values are used. In the active mode, the active and reactive power are changed to decrease the rotor current and boost the PCC voltage, respectively. Based on the control strategy, in a faulty grid, DFIG not only will be able to smooth DC-link voltage fluctuations and reduces rotor overcurrents but also it will increase the voltage of point of common coupling (PCC). Therefore, it improves transient voltage stability. The simulation results show the effectiveness of the proposed strategy for improving voltage stability in the DFIG.
R. Rezavandi, D. A. Khaburi, M. Siami, M. Khosravi, S. Heshmatian,
Volume 17, Issue 2 (6-2021)
Abstract
Recently, Brushless Cascaded Doubly Fed Induction Generator (BCDFIG) has been considered as an attractive choice for grid-connected applications due to its high controllability and reliability. In this paper, a Finite Control Set Model Predictive Control (FCS-MPC) method with active and reactive power control capability in grid-connected mode is proposed for controlling the BCDFIG in a way that notable improvement of the dynamic response, ripple reduction of the active and reactive power waveforms and also better THD performance are achieved compared to the traditional approaches such as Vector Control (VC) method. For this purpose, the required mathematical equations are obtained and presented in detail. In order to validate the proposed method performance, a 1–MW grid-connected BCDFIG is simulated in MATLAB/Simulink environment.
