Abstracts – Browse Results
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Brager, G, Zhang, H and Arens, E (2015) Evolving opportunities for providing thermal comfort. Building Research & Information, 43(03), 274-87.
de Dear, R, Kim, J, Candido, C and Deuble, M (2015) Adaptive thermal comfort in Australian school classrooms. Building Research & Information, 43(03), 383-98.
Farnham, C, Emura, K and Mizuno, T (2015) Evaluation of cooling effects: outdoor water mist fan. Building Research & Information, 43(03), 334-45.
Gauthier, S and Shipworth, D (2015) Behavioural responses to cold thermal discomfort. Building Research & Information, 43(03), 355-70.
Hellwig, R T (2015) Perceived control in indoor environments: a conceptual approach. Building Research & Information, 43(03), 302-15.
Mavrogianni, A, Taylor, J, Davies, M, Thoua, C and Kolm-Murray, J (2015) Urban social housing resilience to excess summer heat. Building Research & Information, 43(03), 316-33.
Parkinson, T and de Dear, R (2015) Thermal pleasure in built environments: physiology of alliesthesia. Building Research & Information, 43(03), 288-301.
Teli, D, James, P A B and Jentsch, M F (2015) Investigating the principal adaptive comfort relationships for young children. Building Research & Information, 43(03), 371-82.
Verhaart, J, Veselý, M and Zeiler, W (2015) Personal heating: effectiveness and energy use. Building Research & Information, 43(03), 346-54.
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0961-3218
- URL: https://doi.org/10.1080/09613218.2015.1001606
- Abstract:
Buildings use approximately 40% of primary energy with most energy expended on the provision of a comfortable indoor climate. An extended range of indoor temperatures can significantly reduce the energy load. However, lower temperature set points for heating can cause thermal discomfort. Giving building occupants the option to warm themselves (e.g. a local source at their desk or workstation) can mitigate this discomfort by the provision of a personalized conditioning system. A model is presented to assess the performance of personalized heating and its impact on the whole building energy load. Researchers, designers and facility managers can use this model to compare performance and analyse energy savings. The total energy use of personalized heating is estimated by scaling its settings to the actual level of discomfort resulting from a lowered heating set point. This model is used to assess seven different personalized heating systems. Assessments reveal that personalized heating brings a remarkable energy-saving potential, while maintaining or even improving individually perceived thermal comfort. Assessments are based on an assumed linear relation between the power and level of increased thermal sensation. Future research in personalized conditioning systems should be directed towards the development of the full characteristics and specific settings.