A Novel Method for Detecting Dust Accumulation in Photovoltaic Systems: Evaluating Visible Sunlight Obstruction in Different Dust Levels and AI-based Bird Droppings Detection

This paper presents an innovative method for automatically detecting dust accumulation on a PV system and notifying the user to clean it instantly. The accumulation of dust, bird, or insect droppings on the surface of photovoltaic (PV) panels creates a barrier between the solar energy and the panel's surface to receive sufficient energy to generate electricity. The study investigates the effects of dust on PV panel output and visible sunlight (VSL) block amounts to utilize the necessity of cleaning and detection. The amount of blocked visible sunlight while passing through glass due to dust determines the accumulated dust level. Visible sunlight can easily pass through the clean, transparent glass but reflects when something like dust obstructs it. Based on those concepts, a system is designed with a light sensor that is simple, effective, easy to install, hassle-free, and can spread the technology. The study also explores the effectiveness of the detection system developed by using image processing and machine learning algorithms to identify dust levels and bird or insect droppings accurately. The experimental setup in Gazipur, Bangladesh, found that excessive dust can block up to 55% of visible sunlight, wasting 55% of solar energy in the visible spectrum, and cleaning can recover 3% of power weekly. The data from the dust detection system is correlated with the 400W capacity solar panels' naturally lost efficiency data to validate the system. This research measured visible sunlight obstruction and loss due to dust. However, the addition of an infrared radiation sensor can draw the entire scenario of energy loss by doing more research.