Open Access
E3S Web Conf.
Volume 312, 2021
76th Italian National Congress ATI (ATI 2021)
Article Number 02001
Number of page(s) 15
Section Energy Efficiency of Buildings
Published online 22 October 2021
  1. [Google Scholar]
  2. ASHRAE Guideline 34P, Energy Guideline for Historical Buildings Second Public Review Draf, [Google Scholar]
  3. F. Ascione, N. Bianco, R.F. De Masi, F. De Rossi, G. P. Vanoli, “Energy retrofit of an educational building in the ancient centre of Benevento. Feasibility study of energy savings and respect of the historical value”, Energy and Buildings Volume 95, 15 May 2015, Pages 172–183 [Google Scholar]
  4. L. Kranzl and The ENTRANZE consortium, Laying Down The Pathways To Nearly Zero-Energy Buildings A toolkit for policy makers, Final Report of the Policies to enforce the transition to nearly zero energy buildings in the EU-27 (ENTRANZE) founded by IEE (2014), [Google Scholar]
  5. [Google Scholar]
  6. [Google Scholar]
  7. [Google Scholar]
  8. [Google Scholar]
  9. [Google Scholar]
  10. [Google Scholar]
  11. [Google Scholar]
  12. [Google Scholar]
  13. [Google Scholar]
  14. [Google Scholar]
  15. [Google Scholar]
  16. C. Reinhart, C. Davila, Urban building energy modeling — A review of a nascent field, Building and Environment 97 (2016), 196–202. [Google Scholar]
  17. Lukas G. Swan, V. IsmetUrgursal, Modeling of end use Energy consumption in the residential sector: A review of modelling techniques, Renewable & Sustainable Energy Reviews 13 (2009) 1819–1835. DOI: 10.1016/j.rser.2008.09.033 [Google Scholar]
  18. Y. Q. Ang, M. Zachary, C. Berzolla, C.F. Reinhart From concept to application: A review of use cases in urban building energy modeling, Applied Energy Volume 279, 1 December 2020, [Google Scholar]
  19. N. Abbasabadi, M. Ashayeri, Urban energy use modelling methods and tools: A review and an outlook, Building and Environment 161 (2019), 106–270, [Google Scholar]
  20. R. Nouvel, A. Mastrucci, U. Leopold, O. Baume, V. Coors, U. Eicker, Combining GIS-based statistical and engineering urban heat consumption models: Towards a new framework for multi-scale policy support, Energy and Buildings 107(2015), 204–212. [Google Scholar]
  21. J. Keirstead, M. Jennings, A. Sivakumar, A review of urban energy system models: Approaches, challenges and opportunities, Renewable and Sustainable Energy Reviews 16 (2012) 3847–3866; https://doi:10.1016/j.rser.2012.02.047 [Google Scholar]
  22. [Google Scholar]
  23. Y. Chen, T. Hong, M. AcPiette, City-scale building retrofit analysis: A case study using CityBES, Build. Simul. (2017), San Francisco, CA, USA. [Google Scholar]
  24. C. Reinhart, T. Dogan, J. A. Jakubiec, T. Rakha, A. Sang, Umi - an urban simulation environment for building energy use, daylighting and walkability. In: Proc BS201313th conference int build performance simulation assoc; 2013. p. 476–83 [Google Scholar]
  25. J. Sokol, C. D. Cerezo, C. Reinhart, Validation of a Bayesian-based method for defining residential archetypes in urban building energy models. Energy and Buildings, Volume 134, 1 January 2017, Pages 11–24, [Google Scholar]
  26. D. Lgs. 192/2005 (and s.m.s) and Italian Standard UNI/TS 11300:2014. [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.