EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 562 (2024) E3S Web of Conf., 562 (2024) 09001 References
Open Access
Issue
E3S Web of Conf.
Volume 562, 2024
BuildSim Nordic 2024
Article Number 09001
Number of page(s) 15
Section Indoor Environmental Quality (IEQ), CFD and Air Flow
DOI https://doi.org/10.1051/e3sconf/202456209001
Published online 07 August 2024
  1. Dupont B, Dietrich K, Dupont B, et al (2014) Impact of residential demand response on power system operation: A Belgian case study Impact of residential demand response on power system operation. Appl Energy 122. https://doi.org/10.1016/j.apenergy.2014.02.022 [CrossRef] [Google Scholar]
  2. Knotzer (2019) Characterization of Energy Flexibility in Buildings [Google Scholar]
  3. Martinez S, Vellei M, Dréau J Le (2022) Energy & Buildings Demand-side flexibility in a residential district: What are the main sources of uncertainty? Energy Build 255,111595. https://doi.org/10.1016/j.enbuild.2021.111595 [CrossRef] [Google Scholar]
  4. Sarran L, Gunay HB, Brien WO, et al (2021) A data-driven study of thermostat overrides during demand response events. Energy Policy 153, 112290 [CrossRef] [Google Scholar]
  5. Li R, Satchwell AJ, Finn D, et al (2022) Ten questions concerning energy flexibility in buildings. Build Environ 223,109461. https://doi.org/10.1016/j.buildenv.2022.109461 [Google Scholar]
  6. Reynders G, Diriken J, Saelens D (2017) Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings. Appl Energy 198,192–202. https://doi.org/10.1016/j.apenergy.2017.04.061 [CrossRef] [Google Scholar]
  7. Deurinck M, Saelens D, Roels S (2012) Assessment of the physical part of the temperature takeback for residential retrofits. Energy Build 52,112–121. https://doi.org/10.1016/j.enbuild.2012.05.024 [CrossRef] [Google Scholar]
  8. Hens H (2010) Installaties: sanitair en gas, 3rd ed. Acco [Google Scholar]
  9. Khan I, Jack MW, Stephenson J (2019) Identifying residential daily electricity-use profiles through time-segmented regression analysis. Energy Build 194,232–246. https://doi.org/10.1016/j.enbuild.2019.04.026 [CrossRef] [Google Scholar]
  10. Ormandy D, Ezratty V (2012) Health and thermal comfort: From WHO guidance to housing strategies. Energy Policy 49,116–121. https://doi.org/10.1016/j.enpol.2011.09.003 [CrossRef] [Google Scholar]
  11. Trotta G, Rhiger A, Sommer S (2022) The price elasticity of residential district heating demand: New evidence from a dynamic panel approach. Energy Econ 112,106163. https://doi.org/10.1016/j.eneco.2022.106163 [CrossRef] [Google Scholar]
  12. Eurostat (2023) Energy consumption in households. https://ec.europa.eu/eurostat/statisticsexplained/index.php?title=Energy_consumption_in_households [Google Scholar]
  13. Flemish Government (2018) Bijlage V Bepalingsmethode EPW Bepalingsmethode van het peil van primaire energieverbruik van residentiële eenheden. 1–169 [Google Scholar]
  14. Lambie E (2021) Evaluation of the Impact of Energy Renovation Measures: Experimental Study of Residential Buildings. KU Leuven [Google Scholar]
  15. TRNSYS (2017) TRNSYS. Transient System Simulation Tool. [Google Scholar]
  16. Belgian Federal Government (2017) Consumer price index. https://statbel.fgov.be/en/themes/consumer-prices/consumer-priceindex#documents [Google Scholar]
  17. Belgian Federal Government (2017) Health index. https://statbel.fgov.be/en/themes/consumer-prices/health-index#documents [Google Scholar]
  18. Bhattacharjee S, Reichard G, McCoy A, et al (2014) Identification of elements to control and regulate residential energy consumption. Advances in Building Energy Research 8,174–195. https://doi.org/10.1080/17512549.2013.865552 [CrossRef] [Google Scholar]
  19. Tweed C, Dixon D, Hinton E, Bickerstaff K (2014) Thermal comfort practices in the home and their impact on energy consumption. Architectural Engineering and Design Management 10,1–24. https://doi.org/10.1080/17452007.2013.837243 [CrossRef] [Google Scholar]
  20. Hwang RL, Lin TP, Cheng MJ, Chien JH (2007) Patient thermal comfort requirement for hospital environments in Taiwan. Build Environ 42,2980–2987. https://doi.org/10.1016/j.buildenv.2006.07.035 [CrossRef] [Google Scholar]
  21. Schellen L, Van Marken Lichtenbelt WD, Loomans MGLC, et al (2010) Differences between young adults and elderly in thermal comfort, productivity, and thermal physiology in response to a moderate temperature drift and a steady-state condition: Differences between young adults and elderly in thermal comfort, productivity, . Indoor Air 20,273–283. https://doi.org/https://doi.org/10.1111/j.1600-0668.2010.00657.x [CrossRef] [PubMed] [Google Scholar]
  22. Ivanko D, Sørensen ÅL, Nord N (2021) Splitting measurements of the total heat demand in a hotel into domestic hot water and space heating heat use. Energy 219. https://doi.org/10.1016/j.energy.2020.119685 [CrossRef] [Google Scholar]
  23. Leiria D, Johra H, Marszal-Pomianowska A, Pomianowski MZ (2023) A methodology to estimate space heating and domestic hot water energy demand profile in residential buildings from low-resolution heat meter data. Energy 263,125705. https://doi.org/10.1016/j.energy.2022.125705 [CrossRef] [Google Scholar]
  24. Zbigniew M, Leiria D, Johra H, et al (2022) Validation of a new method to estimate energy use for space heating and hot water production from low-resolution heat meter data. BuildSim Nordic Conference 2022 (p. 10001). EDP Sciences. [Google Scholar]
  25. Hens H, Parijs W, Deurinck M (2010) Energy consumption for heating and rebound effects. Energy Build 42,105–110. https://doi.org/10.1016/j.enbuild.2009.07.017 [CrossRef] [Google Scholar]
  26. Zheng S, Qi Q, Sun Y, Ai X (2023) Integrated demand response considering substitute effect and time-varying response characteristics under incomplete information. Appl Energy 333,120594 [CrossRef] [Google Scholar]
  27. Baetens R, Saelens D (2016) Modelling uncertainty in district energy simulations by stochastic residential occupant behaviour. J Build Perform Simul 9,431–447. https://doi.org/10.1080/19401493.2015.1070203 [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.