An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity

In this paper, with the assistance of some tools and a machine learning model, smart wind turbine was formed that eliminates expensive sensors reduces sensor complexity. Squirrel cage induction generator (SCIG) six rotor blades make up proposed design, depending on wind's direction, itself can rotate hub to produce energy more effectively. Additionally, two stepper motors are coupled yaw mechanism aid hub, entire controlling procedure will depend direction wind. The must continuously revolve in same as maximize utilization. correctly predict degrees, model deployed. Random forest regression used train direction. is deployed Raspberry Pi, where incoming values being stored. Using generated data, trained it be concluded potentially replace reduce cost. for similar weather conditions only based fewer sensors.