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

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 The Authors, published by EDP Sciences