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Nowadays, wind turbine energy has an increased importance in electrical power applications since when it is considered as an essential inexhaustible and broadly available energy resource. An aerogenerator is a device that transforms a part of the kinetic energy of the wind into available mechanical energy on a transmission shaft, and then into electrical energy through a generator, which is in our case a dual power asynchronous machine. An important characteristic of a wind turbine is that the avail, able maximum power is provided only in a single given operating point, called Maximum Power Point. Many classical methods and controllers have been widely developed and implemented to track the maximum power point. Among drawbacks of a classical PI controller is that its parameters are not constant, these conventional control laws may be are insufficient because they are not robust, especially when the accuracy requirements and other dynamic characteristics of the system are strict. The new idea in this paper is to introduce the Genetic Algorithms theory into the controlstrategy that used inthe conversion chain of the wind turbine, in order to improve stability. Simulation results approve that the application of Genetic Algorithms to the PI regulator, minimize or eliminate the drawbacks of the classical PI regulator, and greatly promote the efficiency and stability of the wind turbine systems.

Optimal tuning of PI controller using genetic algorithm for wind turbine application