The rapid growth of renewable energy sources, including wind power, has created a strong imperative for efficient and reliable infrastructure maintenance. This paper introduces a distributed system framework for UAV-based inspection of renewable energy facilities, with a focus on wind turbines. This framework combines the power of UAVs that have high resolution, thermal imaging, and visual sensors within a modular architecture for real-time collection, processing, and detection of defects. With the utilization of distributed computing and intelligent algorithms, this system reduces operational inefficiencies caused by the manual traditional method while enhancing the accuracy of inspections. An experimental study conducted at a wind power plant demonstrates the effectiveness of the system, achieving up to 94% defect detection accuracy while reducing inspection time per turbine to 1.5 hours. The proposed framework minimizes human intervention, enhances safety, and provides a cost-effective solution for monitoring large-scale renewable energy assets, contributing to the sustainability and reliability of modern energy infrastructure

Distributed Systems, UAV Inspection, Renewable Energy Infrastructure, Wind Turbine Maintenance, Intelligent Monitoring Systems, Sustainable Energy Solutions