Open Access
Issue
E3S Web Conf.
Volume 263, 2021
XXIV International Scientific Conference “Construction the Formation of Living Environment” (FORM-2021)
Article Number 04016
Number of page(s) 13
Section Engineering and Smart Systems in Construction
DOI https://doi.org/10.1051/e3sconf/202126304016
Published online 28 May 2021
  1. Chicherin, S. V. Comparison of a district heating system operation based on actual data – Omsk city, Russia, case study. Int. J. Sustain. Energy 38, 603–614 (2019). [CrossRef] [Google Scholar]
  2. Chicherin, S., Junussova, L. & Junussov, T. Advanced Control of a District Heating System with High Residential Domestic Hot Water Demand. E3S Web Conf. 160, (2020). [Google Scholar]
  3. Buffa, S., Cozzini, M., D’Antoni, M., Baratieri, M. & Fedrizzi, R. 5th generation district heating and cooling systems: A review of existing cases in Europe. Renew. Sustain. Energy Rev. 104, 504–522 (2019). [Google Scholar]
  4. Chicherin, S., Junussova, L. & Junussov, T. Study on the modernisation of an extra-worn district heating (DH) system in Russia: low temperature DH and 4 more options processing. E3S Web Conf. 143, (2020). [Google Scholar]
  5. Farouq, S., Byttner, S., Bouguelia, M.-R., Nord, N. & Gadd, H. Large-scale monitoring of operationally diverse district heating substations: A reference-group based approach. Eng. Appl. Artif. Intell. 90, 103492 (2020). [CrossRef] [Google Scholar]
  6. Braas, H., Jordan, U., Best, I., Orozaliev, J. & Vajen, K. District heating load profiles for domestic hot water preparation with realistic simultaneity using DHWcalc and TRNSYS. Energy 117552 (2020) doi:10.1016/J.ENERGY.2020.117552. [Google Scholar]
  7. Kristensen, M. H., Hedegaard, R. E. & Petersen, S. Long-term forecasting of hourly district heating loads in urban areas using hierarchical archetype modeling. Energy 201, (2020). [Google Scholar]
  8. Volkova, A. et al. Energy cascade connection of a low-temperature district heating network to the return line of a high-temperature district heating network. Energy 198, 117304 (2020). [CrossRef] [Google Scholar]
  9. Chicherin, S., Junussova, L., Junussov, T. & Junussov, C. Comparing strategies for improving thermal performance of an existing district heating (DH) network: low temperature DH in Omsk, Russia. E3S Web Conf. 173, (2020). [Google Scholar]
  10. Meesenburg, W., Ommen, T., Thorsen, J. E. & Elmegaard, B. Economic feasibility of ultra-low temperature district heating systems in newly built areas supplied by renewable energy. Energy 191, 116496 (2020). [CrossRef] [Google Scholar]
  11. Arabkoohsar, A. & Alsagri, A. S. A new generation of district heating system with neighborhood-scale heat pumps and advanced pipes, a solution for future renewable-based energy systems. Energy 193, 116781 (2020). [CrossRef] [Google Scholar]
  12. Harney, P., Gartland, D. & Murphy, F. Determining the optimum low-temperature district heating network design for a secondary network supplying a low-energy-use apartment block in Ireland. Energy 192, (2020). [Google Scholar]
  13. Saletti, C., Zimmerman, N., Morini, M., Kyprianidis, K. & Gambarotta, A. Enabling smart control by optimally managing the State of Charge of district heating networks. Appl. Energy 116286 (2020) doi:https://doi.org/10.1016/j.apenergy.2020.116286. [Google Scholar]
  14. Barone, G., Buonomano, A., Forzano, C. & Palombo, A. A novel dynamic simulation model for the thermo-economic analysis and optimisation of district heating systems. Energy Convers. Manag. 220, (2020). [Google Scholar]
  15. Wirtz, M., Kivilip, L., Remmen, P. & Müller, D. 5th Generation District Heating: A novel design approach based on mathematical optimization. Appl. Energy 260, 114158 (2020). [CrossRef] [Google Scholar]
  16. Jebamalai, J. M., Marlein, K. & Laverge, J. Influence of centralized and distributed thermal energy storage on district heating network design. Energy 202, (2020). [Google Scholar]
  17. Guelpa, E. Impact of thermal masses on the peak load in district heating systems. Energy 214, (2021). [Google Scholar]
  18. Luc, K. M., Li, R., Xu, L., Nielsen, T. R. & Hensen, J. L. M. Energy flexibility potential of a small district connected to a district heating system. Energy Build. 225, (2020). [Google Scholar]
  19. Turski, M. & Sekret, R. Buildings and a district heating network as thermal energy storages in the district heating system. Energy Build. 179, 49–56 (2018). [CrossRef] [Google Scholar]
  20. Vandermeulen, A., Van Oevelen, T., van der Heijde, B. & Helsen, L. A simulation- based evaluation of substation models for network flexibility characterisation in district heating networks. Energy 201, (2020). [Google Scholar]
  21. Hammer, A., Sejkora, C. & Kienberger, T. Increasing district heating networks efficiency by means of temperature-flexible operation. Sustain. Energy, Grids Networks 16, 393–404 (2018). [CrossRef] [Google Scholar]
  22. Chicherin, S., Junussova, L. & Junussov, T. Minimizing the supply temperature at the district heating plant – dynamic optimization. E3S Web Conf. 118, (2019). [Google Scholar]
  23. Chicherin, S., Junussova, L., Junussov, T. & Junussov, C. Optimizing Industrial Facility’s Demand for Combined Heat-and-Power (CHP). in Sustainable Development of Water and Environment (ed. Jeon, H.-Y.) 287–295 (Springer International Publishing, 2020). [CrossRef] [Google Scholar]
  24. Junussova, L., Zhuikov, A., Matiushenko, A., Chicherin, S. & Ilicheva, A. Assessing building energy efficiency with the help of specific heat demand characteristics: boreal regions of Russia case study. E3S Web Conf. 208, (2020). [Google Scholar]
  25. Leśko, M., Bujalski, W. & Futyma, K. Operational optimization in district heating systems with the use of thermal energy storage. Energy 165, 902–915 (2018). [CrossRef] [Google Scholar]

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