EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 362 (2022) E3S Web Conf., 362 (2022) 06007 References
Open Access
Issue
E3S Web Conf.
Volume 362, 2022
BuildSim Nordic 2022
Article Number 06007
Number of page(s) 7
Section Thermal Storage
DOI https://doi.org/10.1051/e3sconf/202236206007
Published online 01 December 2022
  1. Greenberg S., Mills E., Tschudi B., Rumsey P., Myatt B. Best practices for data centers: Lessons learned from benchmarking 22 data centers. Proceedings of the ACEEE Summer Study on Energy Efficiency in Buildings in Asilomar, CA ACEEE, August. 2006;3:76–87. [Google Scholar]
  2. Huang P., Copertaro B., Zhang X., Shen J., Löfgren I., Rönnelid M., et al. A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating. Applied Energy. 2020;258:114109. [CrossRef] [Google Scholar]
  3. Wahlroos M., Pärssinen M., Manner J., Syri S. Utilizing data center waste heat in district heating-Impacts on energy efficiency and prospects for low-temperature district heating networks. Energy. 2017;140:1228–38. [CrossRef] [Google Scholar]
  4. Davies G., Maidment G., Tozer R. Using data centres for combined heating and cooling: An investigation for London. Applied Thermal Engineering. 2016;94:296–304. [CrossRef] [Google Scholar]
  5. He, Z., Ding, T., Liu, Y., Li, Z. Analysis of a district heating system using waste heat in a distributed cooling data center. Applied Thermal Engineering. 2018;141:1131–40. [CrossRef] [Google Scholar]
  6. Drgoňa J., Arroyo J., Cupeiro Figueroa I., Blum D., Arendt K., Kim D., et al. All you need to know about model predictive control for buildings. Annual Reviews in Control. 2020;50:190–232. [CrossRef] [Google Scholar]
  7. Killian M., Kozek M. Ten questions concerning model predictive control for energy efficient buildings. Building and Environment. 2016;105:403–12. [CrossRef] [Google Scholar]
  8. Li H., Nord N. Transition to the 4th generation district heating-possibilities, bottlenecks, and challenges. Energy Procedia. 2018;149:483–98. [CrossRef] [Google Scholar]
  9. Nord N., Shakerin M., Tereshchenko T., Verda V., Borchiellini R. Data informed physical models for district heating grids with distributed heat sources to understand thermal and hydraulic aspects. Energy. 2021;222:119965. [CrossRef] [Google Scholar]
  10. Guan J., Nord N., Chen S. Energy planning of university campus building complex: Energy usage and coincidental analysis of individual buildings with a case study. Energy and Buildings. 2016;124:99–111. [CrossRef] [Google Scholar]
  11. Li H., Hou J., Hong T., Ding Y., Nord N. Energy, economic, and environmental analysis of integration of thermal energy storage into district heating systems using waste heat from data centres. Energy. 2021;219:119582. [CrossRef] [Google Scholar]
  12. Li H., Hou J., Tian Z., Hong T., Nord N., Rohde D. Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage. Energy. 2022;239:122103. [CrossRef] [Google Scholar]
  13. Shu H.-W., Duanmu L., Zhu Y.-X., Li X.-L. Critical COP value of heat pump unit for energy-saving in the seawater-source heat pump district heating system and the analysis of its impact factors. Harbin Gongye Daxue Xuebao(Journal of Harbin Institute of Technology). 2010;42(12):1995–8. [Google Scholar]
  14. Liu X., Zheng O.N., Niu F. A simulation-based study on different control strategies for variable speed pump in distributed ground source heat pump systems. ASHRAE Transactions. 2016;122. [Google Scholar]
  15. Grundfos. Circulator pump, https://product-selection.grundfos.com/no/products/nbg-nbge/nbg/nbg-100-80-160177-97839346?pumpsystemid=1406357823&tab=variant-sizing-results; 2021 [accessed 15 December 2021]. [Google Scholar]
  16. Norwegian Water Resources and Energy Directorate. Energy Regulatory Authority, https://www.nve.no/reguleringsmyndigheten/kunde/nett/nettleie/?ref=mainmenu; 2021 [Accessed 3 November 2021]. [Google Scholar]
  17. Karlsen S.S. Investigation of Grid Rent Business Models as Incentive for Demand-Side Management in Buildings-A case study on fully electric operated houses in Norway. Master thesis: Norwegian University of Science and Technology. 2018. [Google Scholar]
  18. Statistics Norway. Energy and Manufacturing, https://www.ssb.no/en/energi-og-industri/artikler-og-publikasjoner/twofold-increase-in-electricity-price-for-households; 2021 [Accessed 3 November 2021]. [Google Scholar]
  19. Energy Facts Norway. Norway's Energy Supply System, https://energifaktanorge.no/en/utskrift/#toc-2; 2021 [Accessed 3 November 2021]. [Google Scholar]
  20. Nord Pool. https://www.nordpoolgroup.com/; 2021 [Accessed 3 November 2021]. [Google Scholar]
  21. Tensio. Grid Rental, https://ts.tensio.no/kunde/nettleie-priser-og-avtaler; 2021 [Accessed 3 November 2021]. [Google Scholar]
  22. Li H., Hou J., Hong T., Nord N. Distinguish between the economic optimal and lowest distribution temperatures for heat-prosumer-based district heating systems with short-term thermal energy storage. Energy. 2022:123601. [CrossRef] [Google Scholar]
  23. Åkesson J., Årzén K.-E., Gäfvert M., Bergdahl T., Tummescheit H. Modeling and optimization with Optimica and JModelica. org—Languages and tools for solving large-scale dynamic optimization problems. Computers & Chemical Engineering. 2010;34(11):1737–49. [CrossRef] [Google Scholar]
  24. Hou J., Li H., Nord N., Huang G. Model predictive control under weather forecast uncertainty for HVAC systems in university buildings. Energy and Buildings. 2021:111793. [Google Scholar]
  25. Statkraft varme at Tronheim. Products and services, https://www.statkraftvarme.no/globalassets/0/statkraft-varme/produkter-og-tjenester/prisark/jan-2021/trondheim-bedrift-uten-volumledd-bt1.pdf; 2021 [accessed 16 December 2021]. [Google Scholar]
  26. NordlysEnergi. Company, https://www.nordlysenergi.com/bedrift; 2021 [accessed 16 December 2021]. [Google Scholar]
  27. Ahmad T., Chen H., Shair J. Water source heat pump energy demand prognosticate using disparate datamining based approaches. Energy. 2018;152:788–803. [CrossRef] [Google Scholar]
  28. Wang J., Li G., Chen H., Liu J., Guo Y., Sun S., et al. Energy consumption prediction for water-source heat pump system using pattern recognition-based algorithms. Applied Thermal Engineering. 2018;136:755–66. [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.