Open Access
E3S Web Conf.
Volume 362, 2022
BuildSim Nordic 2022
Article Number 13002
Number of page(s) 7
Section Commissioning and Demand Response
Published online 01 December 2022
  1. Ala-Kotila, P., Vainio, T. & Heinonen, J. (2020). Demand Response in District Heating Market—Results of the Field Tests in Student Apartment Buildings. Smart Cities 3(2), 157–171. [CrossRef] [Google Scholar]
  2. Alimohammadisagvand, B., Jokisalo, J. & Sirén, K. (2018). Comparison of four rule-based demand response control algorithms in an electrically and heat pump-heated residential building. Applied Energy 209, 167–179. [CrossRef] [Google Scholar]
  3. Blazejczak, J., Braun, F. G., Edler, D. & Schill, W. P. (2014). Economic effects of renewable energy expansion: A model-based analysis for Germany. Renewable and Sustainable Energy Reviews 40, 1070–1080. [CrossRef] [Google Scholar]
  4. CEN (The European Committee for Standardization) (2007). Ventilation for non-residential buildingsperformance requirements for ventilation and roomconditioning systems (EN. 2007. 13779: 2007). [Google Scholar]
  5. Dominković, D. F., Gianniou, P., Münster, M., Heller, A. & Rode, C. (2018). Utilizing thermal building mass for storage in district heating systems: Combined building level simulations and system level optimization. Energy 153, 949–966. [CrossRef] [Google Scholar]
  6. European Commission. (2018a). EU Climate Action -2030 climate and energy framework. Accessed December 9, (2020). [Google Scholar]
  7. European Commission. (2018b). Heating and cooling. Accessed December 9, 2020. [Google Scholar]
  8. European Commission. (2020). 2050 long-term strategy. Accessed December 9, 2020. [Google Scholar]
  9. Johra, H., Heiselberg, P. & Le Dréau, J. (2019). Influence of envelope, structural thermal mass and indoor content on the building heating energy flexibility. Energy and Buildings 183, 325–339. [CrossRef] [Google Scholar]
  10. Ju, Y., Jokisalo, J., Kosonen, R., Kauppi, V. & Janßen, P. (2021). Analyzing power and energy flexibilities by demand response in district heated buildings in Finland and Germany. Science and Technology for the Built Environment 27(10), 1440–1460. [CrossRef] [Google Scholar]
  11. Kontu, K., Vimpari, J., Penttinen, P. & Junnila, S. (2018). City scale demand side management in three differentsized district heating systems. Energies, 11(12), 3370. [CrossRef] [Google Scholar]
  12. Le Dréau, J. & Heiselberg, P. 2016. Energy flexibility of residential buildings using short term heat storage in the thermal mass. Energy 111, 991–1002. [CrossRef] [Google Scholar]
  13. Loga, T. & Imkeller-Benjes, U. (1997). Energiepass Heizung/Warmwasser [Energy demand heating/hot water]. Institut Wohnen und Umwelt (IWU). Darmstadt. Accessed March 5, 2021. [Google Scholar]
  14. Martin, K. (2017). Demand Response of Heating and Ventilation within Educational Office Buildings. Master’s Thesis. Aalto University. [Google Scholar]
  15. Reynders, G., Diriken, J. & Saelens, D. (2017). Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings. Applied Energy 198, 192–202. [CrossRef] [Google Scholar]
  16. SFS (Finnish Standards Association) (2019). Energy performance of buildings. Ventilation for buildings. Part 1: Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. Module M1-6 (EN 16798-1). [Google Scholar]
  17. Stinner, S., Huchtemann, K. & Müller, D. (2016). Quantifying the operational flexibility of building energy systems with thermal energy storages. Applied Energy 181, 140–154. [CrossRef] [Google Scholar]
  18. Suhonen, J., Jokisalo, J., Kosonen, R., Kauppi, V., Ju, Y. & Janßen, P. (2020). Demand Response Control of Space Heating in Three Different Building Types in Finland and Germany. Energies 13(23), 6296. [CrossRef] [Google Scholar]
  19. Tereshchenko, T. & Nord, N. 2016. Energy planning of district heating for future building stock based on renewable energies and increasing supply flexibility. Energy 112, 1227–1244. [CrossRef] [Google Scholar]
  20. Tillmann, P. (2017). Entwicklung einer Einsatzoptimierung von Wärmeerzeugern zur wirtschaftlichen Bewertung unterschiedlicher Integrationskonzepte tiefer Geothermie in einem Nahwärmenetz (Development of an optimization for the use of heat generation units for the economic evaluation of different integration concepts of deep geothermal energy in a local heating network). Master’s Thesis. Hamburg University of Applied Sciences. Unpublished. [Google Scholar]
  21. Vand, B., Martin, K., Jokisalo, J., Kosonen, R. & Hast, A. (2020). Demand response potential of district heating and ventilation in an educational office building. Science and Technology for the Built Environment 26(3), 304–319. [CrossRef] [Google Scholar]
  22. Vattenfall Wärme Hamburg GmbH. Preisblatt 2. Quartal 2019. (Price sheet 2nd Quarter 2019). (2019). Accessed March 7, 2020. [Google Scholar]
  23. Wu, Y., Mäki, A., Jokisalo, J., Kosonen, R., Kilpeläinen, S., Salo, S., & Li, B. (2020). Demand response of district heating using model predictive control to prevent the draught risk of cold window in an office building. Journal of Building Engineering 33, 101855. [Google Scholar]

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