In February, scientists from Tsinghua University and the National Tibetan Plateau Data Centre unveiled findings from a research study, showcasing a new artificial intelligence model that can potentially be used to enhance the efficiency of double-sided solar panels.
According to the study published in the Journal for Remote Sensing, the scientists used machine learning models and data augmentation techniques to analyze sunshine duration data collected from over 2,453 weather stations throughout China. The application of machine learning algorithms effectively overcame the limitations posed by sparse and unevenly distributed ground-based observations, enabling the team to predict solar radiation patterns with unprecedented accuracy.
Photovoltaic (PV) panels, also referred to as solar panels, are designed to convert sunlight directly into electricity using semiconductor materials. When sunlight strikes a PV panel, it energizes the…
