Humans spend most of their time indoors, whether in their place of residence or work, with large amounts of energy consumed to create comfortable living conditions. Buildings are, therefore, accountable for a considerable proportion of global energy demand; within them, heating, ventilation, and air-conditioning systems constitute major energy drains. Traditionally, these systems are controlled by conventional, mainly static set points, but research has shown that substantial energy savings can be achieved by applying adaptive ones. This work aims to showcase the lower energy consumption achievable when employing adaptive over static approaches, using empirical data from a non-residential living lab. Assessments of rational and adaptive thermal comfort indices over the energy used in HVAC systems are provided, and the energy-saving potential of adaptive thermal comfort models in the design of HVAC control algorithms is estimated. The findings of this work highlight that controlling indoor setpoint temperature according to the adaptive comfort model can achieve energy savings from 15% up to 33%, compared to the rational one, while providing a satisfactory thermal environment.

Indoor thermal comfort analysis for developing energy-saving strategies in buildings

Silvia Erba;
2023-01-01

Abstract

Humans spend most of their time indoors, whether in their place of residence or work, with large amounts of energy consumed to create comfortable living conditions. Buildings are, therefore, accountable for a considerable proportion of global energy demand; within them, heating, ventilation, and air-conditioning systems constitute major energy drains. Traditionally, these systems are controlled by conventional, mainly static set points, but research has shown that substantial energy savings can be achieved by applying adaptive ones. This work aims to showcase the lower energy consumption achievable when employing adaptive over static approaches, using empirical data from a non-residential living lab. Assessments of rational and adaptive thermal comfort indices over the energy used in HVAC systems are provided, and the energy-saving potential of adaptive thermal comfort models in the design of HVAC control algorithms is estimated. The findings of this work highlight that controlling indoor setpoint temperature according to the adaptive comfort model can achieve energy savings from 15% up to 33%, compared to the rational one, while providing a satisfactory thermal environment.
2023
2023 International Conference on Future Energy Solutions (FES)
979-8-3503-3230-8
ASHRAE Likelihood of dissatisfaction
energy savings
smart buildings
thermal comfort
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1260452
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