The COVID-19 pandemic is changing the way individuals, worldwide, feel about staying in public indoor spaces. A strict control of indoor air quality and of people's presence in buildings will be the new normal, to ensure a healthy and safe environment. Higher ventilation rates with fresh air are expected to be a requirement, especially in educational buildings, due to their high crowding index and social importance. Yet, in this framework, an increased use of primary energy may be overlooked. This paper offers a methodology to efficiently manage complex HVAC systems in educational buildings, concurrently considering the fundamental goals of occupants' health and energy sustainability. The proposed fourstep procedure includes: dynamic simulation of the building, to generate synthetic energy loads; clustering of the energy data, to identify and predict typical building use profiles; day-ahead planning of energy dispatch, to optimize energy efficiency; dynamic adjustment of air changes, to guarantee a safe indoor air quality. Clustering and forecasting energy needs are expected to become particularly effective in a highly regulated context. The technique has been tested on two university classroom buildings, considering pre-lockdown attendance. This notwithstanding, quality and significance of the obtained thermal energy clusters push towards a benchmark post-pandemic application.

Clustering of educational building load data for defining healthy and energy-efficient management solutions of integrated HVAC systems

Testi D.
Primo
;
Franco A.
Secondo
;
Conti P.
Penultimo
;
Bartoli C.
Ultimo
2020-01-01

Abstract

The COVID-19 pandemic is changing the way individuals, worldwide, feel about staying in public indoor spaces. A strict control of indoor air quality and of people's presence in buildings will be the new normal, to ensure a healthy and safe environment. Higher ventilation rates with fresh air are expected to be a requirement, especially in educational buildings, due to their high crowding index and social importance. Yet, in this framework, an increased use of primary energy may be overlooked. This paper offers a methodology to efficiently manage complex HVAC systems in educational buildings, concurrently considering the fundamental goals of occupants' health and energy sustainability. The proposed fourstep procedure includes: dynamic simulation of the building, to generate synthetic energy loads; clustering of the energy data, to identify and predict typical building use profiles; day-ahead planning of energy dispatch, to optimize energy efficiency; dynamic adjustment of air changes, to guarantee a safe indoor air quality. Clustering and forecasting energy needs are expected to become particularly effective in a highly regulated context. The technique has been tested on two university classroom buildings, considering pre-lockdown attendance. This notwithstanding, quality and significance of the obtained thermal energy clusters push towards a benchmark post-pandemic application.
2020
Testi, D.; Franco, A.; Conti, P.; Bartoli, C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1062520
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