Future Directions in Wind Energy: Automation, Robotic Maintenance, and Cutting-Edge Communication Solutions
DOI:
https://doi.org/10.13052/jmm1550-4646.213421Keywords:
Wind turbine automation, robotic networking, predictive maintenance, AI and machine learning, sensor networksAbstract
The increasing need for renewable energy has catalyzed advancements in wind turbine technology, especially in automation and robotic networking for the monitoring and control of wind turbines. This article discusses about the innovative turbine control techniques, that optimize efficiency, decrease the maintenance expenses, and improve safety. The integration of Automation and AI/ML facilitate predictive maintenance and offers robust control systems. Advanced control algorithms enhance turbine performance through wake steering, yaw alignment, and shadow flicker reduction. Real-time data sharing and guaranteed connectivity are enabled by wireless sensor networks and communication infrastructures, including Long Term Evolution (LTE), 5G, and Ethernet passive optical networks (EPON). Robots systems as, BladeBUG inspection robot and the Aerones cleaning robot execute efficient autonomous maintenance tasks. Emerging trends depend on AI/ML-driven predictive analytics and flexibility in robotics to enhance turbine performance, reduce downtime, and ensure the reliability of wind power supply.
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