Active and Reactive Power Control for DFIG Using PI, Fuzzy Logic and Self-Tuning PI Fuzzy Controllers

Abstract

This paper presented a system consists of wind turbine operating under the wind speed change, doubly fed induction generator (DFIG) connected directly to the constant grid by the stator and fed by a power converter on the rotor side. Vector control is used to independently control the flow of active and reactive power between the stator of the (DFIG) and the grid, which in this paper is realized, with conventional PI, fuzzy logic and fuzzy self-tuning PI controllers. The proposed controllers generate the references rotor voltages required to guarantee active and reactive power reach their desired reference values. Modeling and simulation of system using MATLAB and their behavior has been examined with simulations. The dynamics of the system is analyzed under varying wind speed, this analysis is focused on the active and reactive power control. The results obtained from PI controller, fuzzy and Fuzzy self tuned PI controllers are compared to validate the advantages of the proposed intelligent controllers based on fuzzy systems.

Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

“…The aerodynamic power P tur captured by the wind turbine is given by [12][13][14][15][16][17][18][19][20][21][22]:…”

“…We present in preferred way the dynamics electrical model of the DFIG-generator in a synchronous reference frame (d, q) rotating at an angular speed of ω s . According to [14][15][16][17][18][19][20][21][22][23], the basic equations used to model the DFIG-generators in the rotating d-q reference frame are written as [24][25][26]:…”

“…The working reference for the control is that related to the rotating field so that the axis (𝑑) coincides with the direction desired flow, which can be rotor, stator, or air gap. Thus, it is possible to orient the different flows of the machine [3,[17][18][19][20][21][22][23][24][25][26][27][28][29].…”

“…The Artificial Neural Network (ANN) is widely used in many fields of technology application and scientific re-search. This technique can be used in cases of difficult problems that cannot be described by precise mathematical approaches where they are very complicated to manipulate [18,20,24] This method was proposed to improve the quality of the current and power generated by the generator-based wind turbine system. The proposed FOC technique is simple to control and easy to implement.…”

DFIG Wind Turbine Controlled by Sliding Mode and Fuzzy-Sliding Control Modes

“…In fact, wind energy systems have high nonlinearity resulting from uncertainties, wind speed turbulence, and changes in wind system parameters [7]. To overcome these perturbations, nonlinear control systems have been designed to be less sensitive to operating conditions variations and system parameters, as fuzzy logic controller [8][9][10][11], sliding mode controller [12][13][14][15][16]. However, addition of a discontinuous control signal to the sliding surface will cause chattering phenomenon.…”