@article{Cao2025, 
author = {Qimeng Cao and Yan Liu and Bing Han and Bingbing Niu and Liu Yang},
title = {Combined empirical model and Euclidean distance for estimating daily and hourly global solar radiation data},
year = {2025},
journal = {Building Simulation},
volume = {18},
number = {11},
pages = {2985-3010},
keywords = {daily global solar radiation, hourly global solar radiation, reference station model, Euclidean distance, sunshine duration},
url = {https://www.sciopen.com/article/10.1007/s12273-025-1355-2},
doi = {10.1007/s12273-025-1355-2},
abstract = {Renewable energy such as solar energy is attracting increasing attention under carbon neutrality. Reliable and precision solar radiation estimations covering county is essential for building performance simulation and solar energy applications. However, existing empirical or reanalysis-based methods for estimating daily and hourly global solar radiation (H and Ih) often oversimplify local climatic effects. Merging the advantage of solar radiation zone and space distance, the reference station model is proposed, which assumes that the solar radiation pattern of the meteorological station is the same as that of the nearest solar radiation station, taking into account spatial distances and similarities in the solar climates. The two-step method of identifying reference station and H and Ih models have been established and analyzed based on 112 solar radiation measurements across China. To verify the accuracy of the reference station model, the comparison is carried out by comparing zone model and individual model. The results show that the minimum Euclidean distance of latitude, altitude and monthly average sunshine duration ratio and the consistent variation trend of monthly average sunshine duration ratio are the criteria for identifying reference station. The sunshine duration ratio is the key index to develop H model. The reference station model demonstrates reliable performance, with the RMSE% of H of 88% stations less than 15%. This work can provide new thoughts and method for improving the solar radiation estimations to assist the low carbon building target.}
}