With the development of metering technologies, data mining techniques such as machine learning have been increasingly used for the prediction of building energy consumption. Among various machine learning methods, the KNN algorithm was implemented to predict the hourly energy consumption of community buildings composed of several different types of buildings. Based on the input data set, 10 similar hourly energy patterns for each season in the historic data sets were chosen, and these 10 energy consumption patterns were averaged. The prediction results were analyzed quantitatively and qualitatively. The prediction results for the summer and fall were close to the energy consumption data, while the results for the spring and winter were higher than the energy consumption data. For accuracy, a similar trend was observed. The values of CVRMSE for the summer and fall were within the acceptable range of ASHRAE guidelines 14, while higher values of CVRMSE for the spring and winter were observed. In sum, the total values of CVRMSE were within the acceptable range.

This study empirically evaluates the energy and carbon reduction effects of an envelope retrofit applied to an aging public building in South Korea. Unlike previous studies that primarily relied on simulation-based analyses, this work fills the empirical research gap by using actual utility billing data collected over one pre-retrofit year (2019) and two post-retrofit years (2023–2024). The retrofit included improvements to exterior walls, roofs, and windows, aiming to enhance thermal insulation and airtightness. The analysis revealed that monthly electricity consumption was reduced by 14.7% in 2023 and 8.0% in 2024 compared to that in the baseline year, with corresponding decreases in electricity costs and carbon dioxide emissions. Seasonal variations were evident: energy savings were significant in the winter due to reduced heating demand, while cooling energy use slightly increased in the summer, likely due to diminished solar heat gains resulting from improved insulation. By addressing both heating and cooling impacts, this study offers practical insights into the trade-offs of envelope retrofitting. The findings contribute to the body of knowledge by demonstrating the real-world performance of retrofit technologies and providing data-driven evidence that can inform policies and strategies for improving energy efficiency in public buildings.

In Korea, green remodeling of public buildings will be mandatory from 2025, and about 30,000 old public buildings nationwide will conduct green remodeling every year. Therefore, in this study, green remodeling was promoted to improve energy efficiency for existing public buildings located in Siheung, Gyeonggi-do. A remodeling method was developed to reduce the cooling and heating load of the building and reduce construction costs. The development technology was applied to the demonstration building to improve the insulation and airtightness performance of the building. In order to analyze the effect of improving the energy performance of the building, the simulation results and energy consumption before and after remodeling were analyzed. The demand for heating energy decreased by about 68.95%, and the demand for cooling energy decreased by 35.21%. According to an analysis of actual energy consumption, the average monthly energy consumption savings from January to September was 17.4%. It was confirmed that the savings were the highest at 35.4% in February, during winter. Applying the remodeling method developed in this study is expected to contribute to reducing greenhouse gas emissions by reducing energy efficiency and energy consumption of existing buildings.

The transition to a net-zero energy system is being promoted in the energy sector, which has led to the creation of energy prosumers. These produce, consume, and trade energy using renewable energy systems installed in buildings or complexes. Here, a community was set as the target to apply the concept of an energy prosumer at the individual building and regional levels. Energy-sharing systems were divided into three categories: energy production, energy storage, and energy management. Energy-sharing systems centered on electrical energy—photovoltaic, battery energy storage, and energy management systems—were installed in two communities located in South Korea, and the energy-sharing effects of the system operation were reported. Monthly power consumption in spring and fall exhibited significant savings of approximately three times that of winter consumption, owing to the energy-sharing systems. Daily hourly power-consumption patterns differed on weekdays and weekends because of the weekday working and building-use hours of the communities. Energy could be shared between communities and buildings because of surplus energy. More surplus power was available for energy sharing on weekends because power consumption was lower. Because energy trading and sharing are restricted, the related laws are being revised. Therefore, a low-carbon community can be realized through surplus energy trading and sharing technology between communities and buildings as renewable energy systems spread owing to low carbonization.