Improvement of the solar radiation prediction accuracy of a light environment simulation according to the positioning of an interpolation application during the process

Light environment is directly related to energy reduction and improving health and quality of life, and interest in it continues to increase. Therefore, in light-environment design, simulation tools are used to predict and evaluate the light environment early in the planning stage of a project. Consequently, scientific simulations are most effective from the early stages of sustainable design. However, choosing which simulation tools to use can be challenging, and the entry barriers to their use can be high; some tools are also more difficult to use. In addition, if there is no weather data available for the area to be analyzed, data from a nearby location is often used instead, which reduces the accuracy of the solar radiation prediction in the simulation. Therefore, this study aimed to reduce the difficulty in using environmental prediction simulation tools by applying adjusted Kriging. This study also attempted to determine where the interpolation method could be best applied in the solar radiation simulation process to produce better prediction results. The experimental results showed that the simulation values were more accurate when calculating the solar radiation by generating sky patches with the original typical meteorological year (TMY) data than by generating them with the interpolated TMY data. This interpolation position and method can increase a simulation's accuracy by creating new weather data in areas where no solar radiation data are available. BUILDIT, as a simulation tool for sustainable urban or building design solutions, applied these techniques, which helped the performance of sustainable designs in the early stages of projects.