Performance assessment of different measured variables from onboard monitoring system to obtain the occupancy patterns of rooms in an office building. (August 2021)

• Record Type: Journal Article
• Authors: Díaz-Hernández, H.P.; Sánchez, M.N.; Olmedo, R.; Villar-Ramos, M.M.; Macias-Melo, E.V.; Aguilar-Castro, K.M.; Jiménez, M.J.
• Is Part Of: Journal of building engineering. Volume 40(2021)
• Publication Date: 2021-08
• Subjects: Building energy -- Sensing occupancy -- On-board monitoring -- Thermal parameters -- Performance indicators; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.102676
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Considering the occupant behaviour as one of the most relevant matters that have an influence in the energy performance of buildings and also, one of the most relevant sources of the performance gap, the research work reported in this paper is focused on measuring the occupancy patterns as a variable that could contribute to overcome these problems. An in-depth work that analyses the suitability of different variables to obtain the occupancy patterns from measurements recorded by on-board monitoring systems is described. The indoor air temperature, the relative humidity, the CO2 concentration and the total electricity consumption measurements have been evaluated as occupancy indicators. The proposed approach has been applied to three rooms of an in-use office building. Said offices have different levels of occupancy and users with different habits. The study is based on selecting 32 months with four winters and four summers from a monitoring campaign from June 2013 to March 2019. The work schedule for the employees has been used as a reference to validate the results. This research demonstrates the capability to obtain occupancy patterns from measuring of the CO2 concentration and the total electricity consumption. The deviation between the occupancy patterns obtained from these variables and the reference schedule is under 10%, and it is lower for the rooms with larger occupancy rates. The proposed approach to obtain the occupancy patterns, together with new, smart and digitalised technologies, can contribute to catalyse the enhanced implementation of modelling techniques for building energy assessment and control. Highlights: Considering offices with different occupancy levels and users with different habits. Several measured variables considered as occupancy indicators. The CO2 concentration and total electricity consumption have given accurate results. Lower deviations are obtained for the rooms with larger occupancy rates. Results and conclusions supported by a long test campaign. June 2013 to March 2019.