Simulation of grid connection and maximum power point tracking control of brushless doubly-fed generator in wind power system

In this paper, based on the analysis of the mathematical model in a common synchronous reference frame of the brushless doubly-fed generator (BDFG), the grid connection strategy and maximum energy extraction control were both analyzed. Besides, the transient simulation of no-load model and generation model of the BDFG have been developed on the MATLAB/Simulink platform. The test results during cutting-in grid confirmed the good dynamic performance of grid synchronization and effective power control approach for the BDFG-based variable speed wind turbines.     

DFIG sliding mode control fed by back-to-back PWM converter with DC-link voltage control for variable speed wind turbine

This paper proposes an indirect power control of doubly fed induction generator (DFIG) with the rotor connected to the electric grid through a back-to-back pulse width modulation (PWM) converter for variable speed wind power generation. Appropriate state space model of the DFIG is deduced. An original control strategy based on a variable structure control theory, also called sliding mode control, is applied to achieve the control of the active and reactive power exchanged between the stator of the DFIG and the grid. A proportional-integral-(PI) controller is used to keep the DC-link voltage constant for a back-to-back PWM converter. Simulations are conducted for validation of the digital controller operation using Matlab/Simulink software.     

Artificial bee colony optimization for economic dispatch with valve point effect

In recent years, various heuristic optimization methods have been proposed to solve economic dispatch (ED) problem in power systems. This paper presents the well-known power system ED problem solution considering valve-point effect by a new optimization algorithm called artificial bee colony (ABC). The proposed approach has been applied to various test systems with incremental fuel cost function, taking into account the valve-point effects. The results show that the proposed approach is efficient and robust when compared with other optimization algorithms reported in literature.     

Doubly-fed induction generator drive based WECS using fuzzy logic controller

The purpose of this paper is to improve the control performance of the variable speed, constant frequency doubly-fed induction generator in the wind turbine generation system by using fuzzy logic controllers. The control of the rotor-side converter is realized by stator flux oriented control, whereas the control of the grid-side converter is performed by a control strategy based on grid voltage orientation to maintain the DC-link voltage stability. An intelligent fuzzy inference system is proposed as an alternative of the conventional proportional and integral (PI) controller to overcome any disturbance, such as fast wind speed variation, short grid voltage fault, parameter variations and so on. Five fuzzy logic controllers are used in the rotor side converter (RSC) for maximum power point tracking (MPPT) algorithm, active and reactive power control loops, and another two fuzzy logic controllers for direct and quadratic rotor currents components control loops. The performances have been tested on 1.5 MW doubly-fed induction generator (DFIG) in a Matlab/Simulink software environment.     

A complete modeling and simulation of DFIG based wind turbine system using fuzzy logic control

The current paper talks about the variable speed wind turbine generation system (WTGS). So, the WTGS is equipped with a doubly-fed induction generator (DFIG) and two bidirectional converters in the rotor open circuit. A vector control (VC) of the rotor side converter (RSC) offers independent regulation of the stator active and reactive power and the optimal rotational speed tracking in the power maximization operating mode. A VC scheme for the grid-side converter (GSC) allows an independent regulation of the active and reactive power to exchange with the grid and sinusoidal supply currents and keeps the DC-link voltage constant. A fuzzy inference system (FIS) is adopted as an alternative of the conventional proportional and integral (PI) controller to reject some uncertainties or disturbance. The performances have been verified using the Matlab/Simulink software.