Developing building shape indexes at the city-scale for understanding building energy consumption

As global warming accelerates, countries are establishing carbon emission limitation policies aimed at reducing greenhouse gas emissions. Efforts from various sectors are necessary to reduce these emissions, and the construction sector is also conducting research to reduce carbon emissions. To carry out such research, data on building energy consumption, attribute information, and shape information are needed. Countries such as the United States, Europe, and Japan have established and maintain building energy datasets. However, in Korea, there is a lack of high-quality energy consumption datasets for domestic buildings. Currently, building energy data systems are managed in a fragmented manner by various institutions and departments, leading to difficulties in data matching due to the absence of a standard schema and the presence of duplicated data. As a result, issues such as the increase of dark data within datasets and inconsistencies in data attributes and definitions arise, making it challenging to collect and analyze the data necessary for national-level building energy and greenhouse gas management.

To address this, Korea is developing integrated management technology for building energy consumption data. Buildings have various factors such as usage, envelope performance, HVAC system performance, occupant schedules, and building shapes, which interact complexly with building energy to produce diverse energy consumption patterns. Among these, building shape is a critical variable that significantly influences energy consumption. The goal of this study is to analyze energy consumption based on the morphological characteristics of buildings and develop a shape index to enhance explanatory power.

We selected Seoul as the target area and developed the shape index for a total of 579,408 buildings. For the development of the index, we collected and preprocessed building shape information based on fragmented public data, including data matching and handling missing data. Based on the processed dataset, we developed the shape index and examined the relationship between building energy consumption and the developed index according to building use, presenting basic statistical measures of the shape index for each building use. This study interprets energy consumption from the perspective of building shape by developing a shape index based on fragmented public data. Through this, we can establish building shape as a numerical index of building energy consumption.