A Drone System for PV Panel Cleaning Based on YOLOv8 and Automated Flight Path Planning

Tianyu Xie; Yutong Jiang; Chenglin Wang; Hongtao Ni

doi:10.6911/WSRJ.202502_11(2).0005

Authors

Tianyu Xie
Yutong Jiang
Chenglin Wang
Hongtao Ni

DOI:

https://doi.org/10.6911/WSRJ.202502_11(2).0005

Keywords:

Drone, Automated Cleaning, Power Generation Efficiency, YOLOv8.

Abstract

As photovoltaic (PV) power generation becomes increasingly important, the cleaning and maintenance of PV modules are critical for improving efficiency and extending lifespan. This paper proposes an automated PV panel cleaning system based on drones, utilizing intelligent cleaning technology to restore the efficiency of PV modules. The system consists of three main components: drones, a ground station, and a hive module. The drones are equipped with cleaning devices, water pumps, and obstacle avoidance radars, enabling autonomous task execution. The ground station uses DJI drone images, GeoServer, and the YOLOv8 algorithm to accurately identify and locate PV panels, generating flight paths automatically. The hive module provides water replenishment and charging for the drones. Experimental results demonstrate that the system effectively removes dust, dirt, and corrosive substances, such as bird droppings and acid rain residues, enhancing power generation efficiency and prolonging the lifespan of PV modules. This system offers an efficient solution for intelligent operation and maintenance of photovoltaic power plants.

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