Open Access
Issue
E3S Web Conf.
Volume 312, 2021
76th Italian National Congress ATI (ATI 2021)
Article Number 09001
Number of page(s) 12
Section Smart Energy Systems
DOI https://doi.org/10.1051/e3sconf/202131209001
Published online 22 October 2021
  1. L. Gelazanskas K.A.A. Gamage, Demand side management in smart grid: A review and proposals for future direction, Sustain Cities Soc, 11, 22–30 (2014) [CrossRef] [Google Scholar]
  2. R. Aazami, K. Aflaki, M.R. Haghifam, A demand response based solution for LMP management in power markets, Int J Electr Power Energy Syst, 33, 125–1132 (2011) [Google Scholar]
  3. IEA. Buildings. A source of enormous untapped efficiency potentia (2021) [Google Scholar]
  4. D. Fischera, H. Madani, On heat pumps in smart grids: A review, Renew. Sustain. Energy Rev, 70, 342–357 (2017) [CrossRef] [Google Scholar]
  5. S. Verbeke, A. Audenaert, Thermal inertia in buildings : A review of impacts across climate and building use. Renew Sustain Energy Rev, 82, 2300–2318. (2020) [Google Scholar]
  6. A. Arteconi, N.J. Hewitt, F. Polonara, Domestic demand-side management (DSM): Role of heat pumps and thermal energy storage (TES) systems, Appl Therm Eng, 51, 155–165 (2013) [CrossRef] [Google Scholar]
  7. C. Yongbao, X. Peng, G. Jiefan, S. Ferdinand, L. Weilin. Measures to improve energy demand flexibility in buildings for demand response (DR): A review, Energy Build, 177, 125–139 (2018) [CrossRef] [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, 251, 113387, (2019) [CrossRef] [Google Scholar]
  9. 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, 50, 101689 (2019) [CrossRef] [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, 194, 116838, (2020) [CrossRef] [Google Scholar]
  11. A. Mugnini, F. Polonara, A. Arteconi, Energy flexibility in residential buildings clusters, E3S Web Conf, 197, 10 (2020) [Google Scholar]
  12. G. Buttitta, W. Turner, D. Finn, Clustering of Household Occupancy Profiles for Archetype Building Models, Energy Procedia, 111, 161–170 (2017) [CrossRef] [Google Scholar]
  13. M. Lutz, Learning Python, (2007) [Google Scholar]
  14. 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]
  15. A. Mugnini, G. Coccia, F. Polonara, A. Arteconi, Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling, Energies, 14, 519 (2021) [CrossRef] [Google Scholar]
  16. UNI/TR, 10349-2. Heating and cooling of buildings - Climatic data - Part 2: Data for design load (2016) [Google Scholar]
  17. Viessmann, VITOCAL 200-S AWB/AWB-AC 201.B04/.B07/.B10/.B13/.B16, Commercial datasheet catalogue (2017) [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.