Open Access
E3S Web Conf.
Volume 197, 2020
75th National ATI Congress – #7 Clean Energy for all (ATI 2020)
Article Number 03002
Number of page(s) 10
Section Management of Energy Supply and Demand. Smart Grid
Published online 22 October 2020
  1. L. Gelazanskas, K.A.A. Gamage, Demand side management in smart grid: A review and proposals for future direction, Sustain. Cities Soc. (2014). [Google Scholar]
  2. IEA, The Critical Role of Buildings. Perspectives for the Clean Energy Transition. Report., (2019) [Google Scholar]
  3. S.Ø. Jensen, A. Marszal-Pomianowska, R. Lollini, W. Pasut, A. Knotzer, P. Engelmann, A. Stafford, G. Reynders, IEA EBC Annex 67 Energy Flexible Buildings, Energy Build. (2017). [Google Scholar]
  4. H. Hao, B.M. Sanandaji, K. Poolla, T.L. Vincent, Aggregate flexibility of thermostatically controlled loads, IEEE Trans. Power Syst. (2015). [Google Scholar]
  5. D. Fischer, H. Madani, On heat pumps in smart grids: A review, Renew. Sustain. Energy Rev. (2017). [Google Scholar]
  6. G. Reynders, R. Amaral Lopes, A. Marszal-Pomianowska, D. Aelenei, J. Martins, D. Saelens, Energy flexible buildings: An evaluation of definitions and quantification methodologies applied to thermal storage, Energy Build. (2018). [PubMed] [Google Scholar]
  7. F. D’Ettorre, M. De Rosa, P. Conti, D. Testi, D. Finn, Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage, Sustain. Cities Soc. (2019). [Google Scholar]
  8. A. Arteconi, A. Mugnini, F. Polonara, Energy flexible buildings: A methodology for rating the flexibility performance of buildings with electric heating and cooling systems, Appl. Energy. (2019). [Google Scholar]
  9. W.J.N. Turner, I.S. Walker, J. Roux, Peak load reductions: Electric load shifting with mechanical pre-cooling of residential buildings with low thermal mass, Energy. (2015). [Google Scholar]
  10. M. Hu, F. Xiao, Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior, Energy. (2020). [Google Scholar]
  11. P. Bacher, H. Madsen, Identifying suitable models for the heat dynamics of buildings, Energy Build. (2011). [Google Scholar]
  12. Un.E. ISO, UNI EN ISO 13790. Energy performance of buildings Calculation of energy use for space heating and cooling, (2008) 1–24 [Google Scholar]
  13. T. energy system Specialists, TRNSYS Software [Google Scholar]
  14. Viessmann, VITOCAL 200-S AWB/AWB-AC 201.B04/ .B07/ .B10 / .B13 /.B16. Commercial datasheet catalogue., (2017) [Google Scholar]
  15. V. Corrado, I. Ballarini, S.P. Corgnati, Typology Approach for Building Stock: D6.2 National scientific report on the TABULA activities in Italy, 2012 [Google Scholar]
  16. UNI/TR 11552, Opaque envelope components of buildings Thermo-physical parameters, (2014) 1–44 [Google Scholar]
  17. UNI/TS 11300-1, Energy performance of buildings Part 1: Evaluation of energy need for space heating and cooling, (2014) [Google Scholar]
  18. UNI/TR, 10349-2. Heating and cooling of buildings Climatic data Part 2: Data for design load., (2016) [Google Scholar]
  19. Meteotest, Meteonorm Software [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.