CIE standard general sky model: A review of research landscape, modelling techniques and building energy applications

Determining the sky distribution is crucial for energy-efficient designs. Measurement practices are the most accurate method for deriving sky distribution data, but this is not available in many locations, creating a significant need for sky models. This study reviewed existing research on sky distribution models using a scientometric and critical approach, with a particular focus on the CIE Standard General Sky model (CSGS). The objectives were to investigate the trend in sky distribution model research and their building energy applications, as well as to examine the research process of developing a CSGS. From the findings, there has been significant growth in sky modelling research especially in Asia and Europe while the Perez All-weather model is the most widely adopted sky model. Moreso, key sky modelling research areas are building performance simulation, machine learning, daylight performance metrics, solar irradiance and daylight modelling, overcast skies, sky luminance measurement and the 15 CIE standard skies. For sky luminance measurement, the sky scanner is mainly used but cameras are also widely adopted recently. It was also observed that the Tregenza and Kittler methods are two widely adopted approaches for determining the 15 CIE standard skies. Further investigations show that feature importance (FI) is crucial in sky modelling and the issue of data imbalance should be considered when developing a model. In addition, sky distribution models are mainly used for analysing daylight performance metrics, simulating daylight and energy, predicting solar irradiance and forecasting PV output. Finally, the application of ML and sky images in sky modelling has gained traction over the years, however, this is currently in an infant stage and therefore requires more research exploration.