earticle

영어

This study aims to propose an appropriate statistical model for predicting the energy consumption of apartment buildings, focusing on the summer season, which has recently been experiencing increasingly poor thermal comfort and prolonged duration. To achieve this, we utilized hourly energy consumption data measured by BEMS(Building Energy Management Systems) from June to October 2023 in an apartment complex in Uijeongbu to develop a time series model. In this study, ARIMA(AutoRegressive Integrated Moving Average Model), SARIMA(Seasonal ARIMA), and SARIMAX(Seasonal ARIMA with eXogenous factors) models were examined, and the SARIMA(1,1,7) × (1,1,2)24 model was found to be the most effective. This model displayed a seasonal cycle somewhat different from previous studies and also showed a slightly different relationship between temperature and energy consumption in apartment buildings. These findings suggest the need for further research using a large dataset based on this study. The results of this research are expected to contribute as a foundational study in researching the balance between real-time energy consumption and renewable energy production during the summer season.