Intelligent system for wind generating plant

This paper proposes a new intelligent system for a wind generating plant with various nonlinear uncertainties. The intelligent system based on neural networks can adaptively control the wind generating plant contained various modeling errors and parametric variations. For increasing learning speed and simplifying an algorithm of the neural networks, a new PD (Proportional Differential) learning rule of the neural networks is derived. In order to explain the validity and the reliability of the intelligent system, it is applied to a simulation model of the wind generating plant with typical nonlinear uncertainties. The simulation results show that the proposed intelligent system is superior and powerful to the generating plant.