Data Analysis for Energy Evaluation of Stockholm Campuses

Abstract: The building sector is a significant contributor to global greenhouse gas emissions, necessitating the development of energy-efficient measures to address environmental concerns. The availability of building energy data sets enables the application of data analysis techniques to assess building energy conditions, providing greater potential for evaluating building energy demands. This research centers on the evaluation of three distinct Campuses in Stockholm, including KTH, Frescati, and Solna buildings. The analysis encompasses two critical dimensions: the first related to energy performance certificates, while the second leverages data from the Akademiska Hus database. The information gathered from the Akademiska Hus database is obtained by using a web application developed at KTH Energy Technology, which was mainly available for internal usage. Examination of energy performance certificates reveals a crucial distinction among buildings concerning their energy utilization, construction year, and activity areas. Buildings categorized with energy performance levels E, F, and G emerge as critical areas demanding urgent evaluations. By inspecting data from the Akademiska Hus database, the study evaluates district heating, district cooling, and electricity variations in relation to outdoor temperature fluctuations during 2022. This analysis uncovers notable anomalies in buildings' energy demands. KTH and Solna buildings present abrupt district cooling and district heating variations, as well as high district cooling values during winter, and high district heating values during summer. While some Frescati and Solna buildings evidence constant district heating and district cooling values as an anomaly, along with high district cooling and district heating values during winter and summer periods, respectively. In conclusion, this study recommends in-depth assessments and the implementation of energyefficient measures for buildings classified with energy performance levels E, F, and G linked to large energy variation anomalies. The aim is to recognize the sources of these anomalies and enhance overall energy performance. Notably, KTH and Solna Campuses are identified as areas warranting immediate attention