Data-driven analysis of electricity use for office buildings: a Norwegian case study

Abstract

Buildings are major consumers of primary energy and main contributors to carbon emission. To improve energy efficiency, it is essential to understand the characteristics of energy use in buildings. This study uses an in-use office building with digital systems for monitoring and control in Trondheim, Norway, as the study case. Based on data collected from this office building, a data-driven analysis was conducted to capture the characteristics of electricity use of different parts in the office building. The approaches used in this study included statistical analysis and polynomial regression. The impact of occupancy level on the total electricity use, the electricity use in office areas, and that in corridors & meeting rooms was also studied. The hourly electricity use profiles were obtained for ventilation fans and the cantina. In the end, the electricity use characteristics and existing issues in this office building were discussed.

Occupancy Prediction in IoT-Enabled Smart Buildings: Technologies, Methods, and Future Directions

“…Commercial smart energy meter According to the study found in [85], there is a noticeable correlation between occupancy and the amount of electricity consumed in various areas of a building, including office space, corridors, and meeting rooms. The authors of [86] proposed a system to predict room occupancy using only data from smart meters to predict whether a room is occupied.…”