Open Access
| Issue |
E3S Web Conf.
Volume 246, 2021
Cold Climate HVAC & Energy 2021
|
|
|---|---|---|
| Article Number | 04001 | |
| Number of page(s) | 8 | |
| Section | Measured Energy Use | |
| DOI | https://doi.org/10.1051/e3sconf/202124604001 | |
| Published online | 29 March 2021 | |
- European Commission, “Energy Performance of Buildings,” 2020. [Online]. Available: https://ec.europa.eu/energy/topics/energy-efficiency/energy-efficient-buildings/energy-performance-buildings-directive_en. [Accessed 9 December 2020]. [Google Scholar]
- M. Thalfeldt, J. Kurnitski and A. Mikola, “Nearly zero energy office building without conventional heating,” Est. J. Eng., vol. 19, no. 4, 2013. [Google Scholar]
- D. Calì, T. Osterhage, R. Streblow and D. Müller, “Energy performance gap in refurbished German dwellings: Lesson learned from a field test,” Energy and Buildings, vol. 127, pp. 1146–1158, 2016. [Google Scholar]
- J. Zhao, B. Lasternas, K. P. Lam, R. Yun and V. Loftness, “Occupant behavior and schedule modeling for building energy simulation through office appliance power consumption data mining,” Energy and Buildings, vol. 82, pp. 341–355, 2014. [Google Scholar]
- S. Gilani and W. O'Brien, “A preliminary study of occupants’ use of manual lighting controls in private offices: A case study,” Energy and Buildings, vol. 159, pp. 572–586, 2018. [CrossRef] [Google Scholar]
- R. M. Tetlow, C. van Dronkelaar, C. P. Beaman, A. A. Elmualim and K. Couling, “Identifying behavioural predictors of small power electricity consumption in office buildings,” Building and Environment, vol. 92, pp. 75–85, 2015. [CrossRef] [Google Scholar]
- E. 16798–1, “Energy performance of buildings - Part 1: Indoor environmental input parameters for design and assessment of energy performance of buildings,” CEN, Brussels, Belgium, 2019. [Google Scholar]
- A. C. Menezes, A. Cripps, R. A. Buswell, J. Wright and D. Bouchlaghem, “Estimating the energy consumption and power demand of small power equipment in office buildings,” Energy and Buildings, vol. 75, pp. 199–209, 2014. [CrossRef] [Google Scholar]
- A. Mahdavi, F. Tahmasebi and M. Kayalar, “Prediction of plug loads in office buildings: Simplified and probabilistic methods,” Energy and Buildings, vol. 129, pp. 322–329, 2016. [CrossRef] [Google Scholar]
- R. C. Team, R: A language and environment for statistical computing, Vienna, Austria: R Foundation for Statistical Computing, 2013. [Google Scholar]
- A. Ferrantelli, K. Ahmed, P. Pylsy and J. Kurnitski, “Analytical modelling and prediction formulas for domestic hot water consumption in residential Finnish apartments,” Energy and Buildings, vol. 143, pp. 53–60, 2017. [CrossRef] [Google Scholar]
- A. Ferrantelli, H. Kuivjõgi, J. Kurnitski and M. Thalfeldt, “Office Building Tenants’ Electricity Use Model for Building Performance Simulations,” Energies, vol. 13, p. 5541, 2020. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.