Modeling hourly solar diffuse fraction on a horizontal surface based on sky conditions clustering

The commonly used diffuse fraction models are generally expressed as a single-value function of clearness index (Kt). Whereas in fact, the same Kt occurring at different times of the day may correspond to different diffuse fraction (Kf). Using a 10-year dataset from 2005 to 2014, this study intended to model hourly solar diffuse fraction based on sky conditions. Five cities in China, including Golmud, Kashgar, Sanya, Wuhan, and Wenjiang, were selected as representatives of five solar climatic zones. The measured radiation data on a horizontal surface were used for k-means clustering of the sky conditions with two factors of Kf and Kt. The results show that the sky conditions could be divided into two groups according to time dimension: the morning (6:00-12:00) and the afternoon (13:00-18:00) segments. Subsequently, a morning-afternoon segmented Kf-Kt model for each zone was constructed based on quartic polynomial regression, with the smallest error rate at a range of 10.4%-28.5%. Comparison with the existing models further validates that the respective models for the morning and afternoon periods can assist in improving the modeling of the hourly solar diffuse fraction on a horizontal surface in variable solar climatic zones.

Automated summary

This study aimed to model hourly solar diffuse fraction based on sky conditions using a 10-year dataset from 2005 to 2014. Five cities in China were selected as representatives of five solar climatic zones. The results showed that the sky conditions could be divided into morning and afternoon segments based on time dimension. The respective models for the morning and afternoon periods were found to improve the modeling of the hourly solar diffuse fraction in different solar climatic zones.