Power Optimization Control Scheme for Doubly Fed Induction Generator Used in Wind Turbine Generators

Abstract

Scientists and researchers are exploring different methods of generating and delivering electrical energy in an economical and reliable way, enabling them to generate electricity focusing on renewable energy resources. All of these possess the natural property of self-changing behavior, so the connection of these separate independent controllable units to the grid leads to uncertainties. This creates an imbalance in active power and reactive power. In order to control the active and reactive power in wind turbine generators with adjustable speed, various control strategies are used to allay voltage and current variations. This research work is focused on the design and implementation of effective control strategies for doubly fed induction generator (DFIG) to control its active and reactive power. A DFIG system with its control strategies is simulated on MATLAB software. To augment the transient stability of DFIG, the simulation results for the active and reactive power of conventional controllers are compared with three types of feed forward neural network controllers, i.e., probabilistic feedforward neural network (PFFNN), multi-layer perceptron feedforward neural network (MLPFFN) and radial basic function feedforward neural network (RBFFN) for optimum performance. Conclusive outcomes clearly manifest the superior robustness of the RBFNN controller over other controllers in terms of rise time, settling time and overshoot value.

A Robust Interval Type-2 Fuzzy Logic Controller for Variable Speed Wind Turbines Based on a Doubly Fed Induction Generator

“…In the literature, there are control strategies such as the vector control concept (voltage orientation or stator flux) combined with various controllers (such as proportionalintegral controllers). Unfortunately, when the internal parameters of the machine change, this control strategy loses his robustness [6,7].…”

“…For this reason, the gearbox (with a gear ratio G) is added in the studied system [14]. The mechanical speed and the generator torque can be expressed as described in Equations ( 5) and (6).…”

“…The DFIG has become widely used due to its efficiency, minimum power losses, robustness, ease of control, reduced cost, and ability to work at a speed that varies by ±33% around the synchronous speed. Moreover, this generator requires only slight maintenance [6]. The studied system is illustrated in Figure 1a.…”

Comparative Analysis of PI and Fuzzy Logic Controller for Grid Connected Wind Turbine

“…Due to the DFIG's effectiveness, minimal power losses, simplicity of operation, reduced cost, and very little maintenance. it has gained widespread application [12]. The integration of large wind power generators into current grids has brought various challenges related to e ciency, reliability, and grid integration.…”

“…This has prompted researchers to propose and develop a variety of control systems that can generate high-quality wind energy [13]. The most used control technique is the PI controller because of its effectiveness under normal conditions and simplicity of usage [12] [14].…”