Condition Monitoring of Arrow Dynamic and Drive Train in Wind Turbine using Artificial Intelligence

In order to be economically competitive, various control systems are used in Wind turbine. These systems makes the wind turbine to work efficiently and produce maximum output at different speed. In this paper an adaptive control based on radial-basis function neural network are used for different operation of variable speed wind turbine including torque control at lower speed, pitch control at higher speed and smooth transition between these two modes. The adaptive neural network control approximates the nonlinear dynamics of wind turbine based on input/output measurement. One of the most important features in the smart gird is to integrate the state-of-the-art communication technologies to increase the electrify generation. In offshore wind farms, data communications would rely on wireless techniques. The wireless communication technology has several advantages over the wires or meter counterpart. However, the impact of atmospheric turbulence on wired must be well understood first. In this project, the performance of wireless links subject to weak influence in generator, turbine is monitored. The metrics are analytically and numerically evaluated.