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Assessing the energy saving potential of using adaptive setpoint temperatures: The case study of a regional adaptive comfort model for Brazil in both the present and the future

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Abstract

It has been found in recent years that using setpoint temperatures based on adaptive thermal comfort models is a successful method of energy conservation. Recent studies using adaptive setpoint temperatures incorporate international models from ASHRAE Standard 55 and EN16798-1. This study, however, has instead considered a regional Brazilian adaptive comfort model. This study investigates the energy demand arising from the use of a local Brazilian comfort model in order to assess the energy implications from the use of the worldwide ASHRAE Standard 55 adaptive model and various fixed setpoint temperatures. All of Brazil’s climate zones, full air-conditioning, mixed-mode building operating modes, present-day climate change scenarios, and future scenarios—specifically Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2050 and 2100—have all been taken into account in building energy simulations. The use of adaptive setpoint temperatures based on the Brazilian local model considering mixed-mode has been found to significantly reduce energy consumption when compared to static setpoint temperatures (average energy-saving values ranging from 52% to 58%) and the ASHRAE 55 adaptive model (average values ranging from 15% to 21%). Considering climate change and the mixed-mode Brazilian model, the overall energy demand for the three groups of climatic zones (annual average outdoor temperatures ≤ 21 °C, > 21 and ≤ 25 °C and > 25 °C) ranged between 2% decrease and 5% increase, 4% and 27% increase, and 13% and 45% increase, respectively. It is concluded as a consequence that setting setpoint temperatures based on the Brazilian local adaptive comfort model is a very efficient energy-saving method.

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Acknowledgements

This study was funded by the Urban Innovative Actions initiative (European Commission), under the research project UIA04-212 Energy Poverty Intelligence Unit (EPIU), the Spanish Ministry of Science and Innovation, under the research project PID2021-122437OA-I00 “Positive Energy Buildings Potential for Climate Change Adaptation and Energy Poverty Mitigation (+ENERPOT)” and the Andalusian Ministry of Development, Articulation of the Territory and Housing, under the research project US.22-02 “Implicaciones en la mitigación del cambio climático y de la pobreza energética mediante nuevo modelo de confort adaptativo para viviendas sociales (ImplicAdapt)”. The authors also acknowledge the support provided by the Thematic Network 722RT0135 “Red Iberoamericana de Pobreza Energética y Bienestar Ambiental (RIPEBA)” financed by the call for Thematic Networks of the CYTED Program for 2021.

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Authors and Affiliations

  1. Department of Electrical Engineering, University Carlos III of Madrid, Madrid, Spain

    Daniel Sánchez-García

  2. Department of Building Simulation, ZEROCEM SL, Seville, Spain

    Daniel Sánchez-García

  3. Department of Building Constructions, University of Granada, Granada, Spain

    David Bienvenido-Huertas

  4. Department of Building Constructions II, University of Seville, Seville, Spain

    Carlos Rubio-Bellido

  5. Section of Design for Sustainability, Department of Civil and Mechanical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark

    Ricardo Forgiarini Rupp

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  1. Daniel Sánchez-García
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  2. David Bienvenido-Huertas
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  3. Carlos Rubio-Bellido
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  4. Ricardo Forgiarini Rupp
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Contributions

Daniel Sánchez-García: conceptualization, methodology, software, formal analysis, investigation, writing—original draft, writing—review & editing. David Bienvenido-Huertas: conceptualization, investigation, formal analysis. Carlos Rubio-Bellido: visualization, investigation, validation. Ricardo Forgiarini Rupp: visualization, investigation, validation.

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Correspondence to Daniel Sánchez-García.

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Sánchez-García, D., Bienvenido-Huertas, D., Rubio-Bellido, C. et al. Assessing the energy saving potential of using adaptive setpoint temperatures: The case study of a regional adaptive comfort model for Brazil in both the present and the future. Build. Simul. 17, 459–482 (2024). https://doi.org/10.1007/s12273-023-1084-3

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