Resilience Improvement for Distributed Renewable Energy Grids: Integration of UAV-Assisted Live-Line Inspection and Real-Time Systems
DOI:
https://doi.org/10.13052/dgaej2156-3306.4122Keywords:
Collaborative inspection of drone clusters, Smart grid system, Fault diagnosis, Elastic assessment system, Multi energy complementary systemAbstract
In the context of global energy transition, distributed renewable energy grids face key issues of insufficient resilience due to frequent equipment failures, complex operating environments, and limitations of traditional operation and maintenance methods. The core objective of this study is to enhance the resilience of this type of power grid, integrate unmanned aerial vehicle assisted live inspection and real-time fault diagnosis technology, and construct a full process solution. In the inspection process, a multi rotor drone equipped with high-definition cameras, infrared thermal imaging devices, and partial discharge sensors is used to conduct uninterrupted inspections of power grid equipment at a flight altitude of 20∼150 m and a speed of 3∼8 m/s. Multiple sources of data such as equipment appearance defects and hot spot distribution are collected 2–4 times a week, covering areas that are difficult for manual access. This significantly improves the efficiency of traditional inspections and provides high timeliness data support for fault diagnosis. Fault diagnosis fusion deep learning technology embeds the Convolutional Block Attention Module (CBAM) into the YOLOv7 model to enhance feature focus, constructs a dual channel Generative Adversarial Network (GAN) combined with Long Short-Term Memory (LSTM) to capture fault timing patterns, and designs a sliding window error correction mechanism to counteract noise interference. In the experiment, the accuracy and recall of this method reached 88.62% mAP@0.5 Significantly superior to existing methods such as BVLOS and SIS. The research results provide strong technical support for the safe and stable operation of distributed renewable energy grids, which helps to improve the reliability and anti-interference ability of the grid, promote the sustainable development of distributed renewable energy grids, and is of great significance for ensuring energy security and addressing climate change.
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