Demand response is an effective method for achieving energy flexibility. By utilizing the thermal properties of the building envelope, energy shifting can be achieved by preheating. In this study, a simulation-based method was used to quantify the energy flexibility of residential buildings in Kitakyushu City, Japan. A rule-based control method was used to control the heating systems, resulting in different heat energy reduction ratio after preheating at different start time during the day. Then, k-means clustering analysis was performed on the energy reduction of different buildings during January. The optimal number of clusters was determined to be two based on the Calinski-Harabasz and Davies-Bouldin indices. The results of the clustering analysis showed that the energy reduction was significantly affected by the thermal insulation properties of the building envelope compared to the thermal mass. In addition, weather conditions also had a significant impact on energy reduction, with higher solar radiation and lower humidity contributing to a significant enhancement of energy reduction effects.
Keywords Demand response, Heating system, Building envelope, Clustering analysis, Weather condition