Suitability Evaluation of Different Measured Variables to Assess the Occupancy Patterns of a Building: Analysis of a Classroom of a School in Madrid during the COVID-19 Pandemic

María Nuria Sánchez, Emanuela Giancola, Silvia Soutullo, Ana Rosa Gamarra, Rafael Olmedo, José Antonio Ferrer and María José Jiménez
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María Nuria Sánchez: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
Emanuela Giancola: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
Silvia Soutullo: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
Ana Rosa Gamarra: Energy Systems Analysis Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
Rafael Olmedo: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
José Antonio Ferrer: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain
María José Jiménez: Energy Efficiency in Buildings Unit, Department of Energy, CIEMAT, E-28040 Madrid, Spain

Energies, 2022, vol. 15, issue 9, 1-15

Abstract: Building occupancy is one of the relevant variables to understand the energy performance of buildings and to reduce the current gap between simulation-based and actual energy performance. In this study, the occupancy of a classroom in an educational center monitored over a full year was experimentally assessed. The classroom had different occupancy levels during the school year, with a theoretical minimum of eleven students, and no occupancy during vacations and weekends. Different variables such as indoor air temperature, relative humidity, CO 2 concentration, overall electrical energy consumption of the educational center, electrical energy consumption of the building in which the monitored classroom is located, and heating energy consumption were recorded. We analyzed which of these variables were possible indicators of classroom occupancy, using the school timetable as a theoretical reference value for the validation of the results. Based on previous studies, one-hour moving averages are used to better identify the occupancy patterns by smoothing the fluctuations that are not a consequence of a change in the classroom occupancy. Histograms of each variable are used to identify the variable ranges associated within the occupancy: occupied or empty. The concentration of CO 2 and electric measurements, identified in previous works as suitable to assess the occupancy patterns of rooms like offices with lower levels of occupancy, are recognized as potential occupancy indicators. It is therefore concluded that a higher level of space occupancy does not affect the result, and the same variables are identified as potential occupancy indicators.

Keywords: occupancy patterns; building energy; monitoring; performance assessment; COVID-19 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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