An evaluation of the influential factors on energy performance: A case study of a shopping mall

Abstract: Shopping malls are becoming more prevalent throughout the world. They have been identified as having high energy use, which is less explored than other building types. There are 357 shopping centers in Sweden, which has doubled in the last five years. Regardless of national differences in shopping mall tenants' demands, shopping malls always tend to have high lighting loads, high population density, and, therefore, a significant air conditioning demand. Therefore, exploring the influential parameters determining shopping malls' energy demand demonstrates how well the building performs. Considering the above, this study aims to analyze a three-year hourly energy demand time series recorded in a relatively large shopping mall in south Sweden. This research aims to fill a gap in the literature as there is a lack of evidence of an in-depth analysis of shopping malls' energy demands and their relationship with independent variables. Energy use data and meteorological data were obtained from a BEM system. The analyses focused on determining the annual energy demands in occupied and unoccupied hours and investigating the correlation between outdoor temperature, cooling degree hour, heating degree hour, occupied/unoccupied hours, time of day, tenant electricity, and observed energy use. A Pearson coefficient correlation was used to estimate the correlation between investigated variables. For distinguishing extreme conditions, clusters of warm months, warmest week, cold months, and coldest week were made. The results indicated that each usage of each energy carrier is dependent on its application and has been impacted by particular parameters. Moreover, analysis of clusters revealed that more extreme conditions affect the strength of correlations. The number of influential parameters is higher in warm conditions than in cold ones. Annual energy demand is even less affected by the studied parameters than the cold conditions. Based on annual assessments, district heating is primarily related to heating degree hours, while in cold conditions, it is mainly dependent on working hours, time of day, and supply airflow. The cooling electricity is positively correlated with cooling degree hour, supply airflow, and negatively correlated with heating degree hour on a yearly basis assessment. Under warm conditions, cooling is correlated to working hours, cooling degree hours, property electricity, tenant electricity, and supply airflow. The property electricity is influenced by working hours, tenant electricity, and supply airflow. Additionally, it is highly correlated with district heating flow in cold conditions and electricity for cooling in warm conditions. The results of this study can be used to assess shopping malls' energy performance by considering the most influential factors in design phases and energy management.