Data-driven analysis of heating and cooling base temperatures for buildings: Case studies in South Korea - Kim, Hye Gi; Kim, Sun Sook; Ahn, Hyeunguk (Energy and Buildings, 2024)
To investigate statistical differences in the heating (Tbh) and cooling base temperatures (Tbc) across various building types, vintages, and sizes, we conducted case studies in Seoul, South Korea, based on data from more than 10,000 buildings. To assess the relative impacts of internal and external loads on Tbh and Tbc, we used a core-to-perimeter zone ratio approximated by the average floor area, defined as the floor area per building floor. Employing the energy signature method, change-point regression, and calendarization, we determined the best-fit change-point model and the corresponding Tbh and Tbc for each building. Our findings revealed statistically significant differences in Tbhs and Tbcs, with variations of up to 6 and 4 °C, respectively, across six building types. Notably, for most building types, Tbh and Tbc decreased as the average floor area increased, possibly influenced by a higher core zone to total area ratio. This highlights the predominant impact of internal loads over external loads. The influence of the average floor area on Tbh and Tbc outweighed that of building vintage, particularly for lodging, medical, and sales facilities, where Tbh and Tbc decreased in the more recent vintage buildings. However, this influence was less pronounced for facilities for senior citizens and children and education and research facilities, possibly due to factors such as diverse building shapes and the thermal preferences of occupants. Although this study focuses on South Korea, our data-driven approach provides statistical evidence for refining base temperature and improving traditional degree-day methods. Our findings suggest the need to establish base temperatures that consider various building types, vintages, and average floor areas, especially for large metropolitan cities where these factors vary widely.
Keywords: Base temperature; Building types; Case-studies; Change-point models; Core-to-perimeter zone ratio; Degree-day method; Energy signature method; Energy signatures; Floor areas; South Korea; ANOVA; Big data; Change-point model; Core-to-perimeter zone ratio; Degree-day method; Energy signature method