A Genetic Algorithm Based on Optimization for Doubly Fed Induction Generator

In this paper, we will be interested in studying a system consisting of a wind turbine operating at variable wind speed, and a two-feed asynchronous machine (DFIG) connected to the grid by the stator and fed by a transducer at the side of the rotor. The conductors are separately controlled for active and reactive power flow between the stator (DFIG) and the grid. The proposed controllers generate reference voltages for the rotor to ensure that the active and reactive power reaches the required reference values, to ensure effective tracking of the optimum operating point and obtaining the maximum electrical power output. Dynamic analysis of the system is performed under the variable wind speed. This analysis is based on active and reactive energy control. The new work in this paper is to introduce theories of genetic algorithms into the control strategy used in the switching chain of wind turbines, to improve performance and efficiency. Simulation results applied to genetic algorithms give greater efficiency, impressive results, and stability to wind turbine systems compared to classic PI regulators. Then, artificial intelligent controls, such as genetic algorithms control, are applied. Results obtained, in Matlab/Simulink environment, show the efficiency of this proposed unit.