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Exploring the energy implications of human thermal adaptation to hot temperatures in present and future scenarios: a parametric simulation study

Author

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  • Sánchez-García, Daniel
  • Bienvenido-Huertas, David
  • Kim, Jungsoo
  • Pisello, Anna Laura

Abstract

Understanding how humans adapt to indoor thermal conditions is crucial for designing spaces that promote well-being while achieving energy efficiency goals. Adaptive setpoint temperatures assume occupants adapt to mechanically conditioned spaces as if they were naturally ventilated. However, a broader perspective beyond specific models and climates is needed. This paper explores the energy implications of adaptive comfort models, analyzing key parameters: gradient, y-intercept, offset from neutrality, and applicability upper limit. The Adaptive-Comfort-Control-Implemented Model (ACCIM) tool and BESOS parametric simulation framework were employed to simulate thousands of variations. Future Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) for 2050 and 2080 were considered. Results highlight that the comfort zone threshold (named ASToffset) has the highest impact on cooling demand, with reductions up to 59 %. Then, 1300 parameter combinations were summarized into 10 adaptation profiles, revealing cooling demand reductions of 1 %–17 % per adaptation level. Adaptation profiles indicate significant energy savings by increasing operative temperatures in hot climates. This study reconciles adaptive comfort and energy efficiency, providing insights into the influence of adaptive comfort equations and the energy implications of varying adaptation levels in current and future climates. Findings support the design of energy-efficient spaces, addressing climate change challenges and improving sustainability.

Suggested Citation

  • Sánchez-García, Daniel & Bienvenido-Huertas, David & Kim, Jungsoo & Pisello, Anna Laura, 2025. "Exploring the energy implications of human thermal adaptation to hot temperatures in present and future scenarios: a parametric simulation study," Energy, Elsevier, vol. 325(C).
  • Handle: RePEc:eee:energy:v:325:y:2025:i:c:s0360544225016718
    DOI: 10.1016/j.energy.2025.136029
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