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Optimal operation of district heating networks through demand response

Year 2019, , 35 - 43, 02.03.2019
https://doi.org/10.5541/ijot.519101

Abstract

In
this paper, an optimization method aiming at minimizing the thermal peaks in
district heating networks is proposed. The method relies on a thermo-fluid
dynamic model of both the supply and return networks and permits to analyse the
opportunities for thermal peak shaving through “virtual storage”. The latter is
obtained through variation of the thermal request profiles of the users. The
presence of a peak in the morning is due to the shut-down or attenuation of the
heating systems during the night, which lead to a dramatical increase of the
thermal request early in the morning. The peak compromises a full exploitation
of cogeneration and renewable plants, that are able to cover just a portion of
the maximum load. Consequently, boilers have to be used, leading the system to
a performance reduction and to an increase of primary energy consumption.
Moreover, the peak makes the possibility of network extension quite difficult,
because of the limitation on mass flow rates in the pipes. For this reason, a
model is developed to make the thermal profile as flat as possible. The model
is applied to a portion of the Turin district heating network, which is the
largest network in Italy. Results show that a reductions between 20% and 42%
are possible, depending on the maximum changes in the schedules which are
allowed.

References

  • Frederiksen S., Werner S., District heating and cooling, Lund Studentlitteratur, 2013.
  • Werner S., International review of district heating and cooling, Energy 2017;137:617631.
  • Sartor K., Thomas D., Dewallef P., A comparative study for simulating heat transport in large district heating networks, International Journal of Heat and Technology 2018;36:301-308.
  • Ancona M.A., Melino F., Peretto A., An optimization procedure for district heating networks, Energy procedia 2014;61:278-281.
  • Bojic M., Trifunovic N., Linear programming optimization of heat distribution in a district-heating system by valve adjustments and substation retrofit, Building and Environment 2000;35:151-159.
  • Koiv T.A., Mikola A., Palmiste U., The new dimensioning method of the district heating network, Applied Thermal Energy 2014;71(1):78-82.
  • Wang H., Yin W., Zhou Z., Lahdelma R., Optimizing the design of a district heating network, Proceedings of ECOS 2015, Pau, France, June 30-July 31.
  • Guelpa E., Mutani G., Todeschi V., Verda V., Reduction of CO2 emissions in urban areas through optimal expansion of existing district heating networks Journal of Cleaner Production 2018;204:117-129.
  • Giraud L., Baviere R., Vallee M., Paulus C., Presentation, validation and application of the DistrictHeating Modelica library, Proceedings of the 11th International Modelica Conference 2015, Versailles, France, September 21-23.
  • Pirouti M., Bagdanavicius A., Wu J., Ekanayake J., Optimization of supply temperature and mass flow rate for a district heating network, Proceedings of ECOS 2012, Perugia, Italy, June 26-29.
  • Lindenberger D., Bruckner T., Groscurth H.M., Kummel R.,¨ Optimization of solar district heating systems: seasonal storage, heat pumps, and cogeneration, Energy 2000;25(7):591-608.
  • Verda V., Colella F., Primary energy savings through thermal storage in district heating networks, Energy 2011;36(7):4278-4286.
  • Guelpa E., Verda V., Optimization of the thermal load profile in district heating networks through “virtual storage” at building level Energy procedia 2016;101:798805.
  • Guelpa, E., Marincioni, L., & Verda, V. (2019). Towards 4th generation district heating: Prediction of building thermal load for optimal management. Energy.
  • Verda V., Guelpa E., Sciacovelli A., Acquaviva A., Patti E., Thermal peak load shaving through users request variations in district heating systems, International Journal of Thermodynamics 2016;19(3):168-176.
  • Guelpa E., Barbero G., Sciacovelli A., Verda V., Peak-shaving in district heating systems through optimal management of the thermal request of buildings, Energy 2017;137:706-714.
  • Guelpa E., Deputato S., Verda V., Thermal request optimization in district heating networks using a clustering approach, Applied Energy 2018;228:608-617.
  • Del Hoyo Arce I., Herrero Lopez S., L´ opez Perez S., R´ am¨ a M., Klobut K., Febres J. A.,¨ Models for fast modelling of district heating and cooling networks, Renewable and Sustainable Energy Reviews 2018;82:1863-1873.
  • Harary F., Graph theory, New Delhi: Narosa Publishing House, 1995.
  • Sciacovelli A., Verda V., Borchiellini R., Numerical design of thermal systems, 2015, CLUT Editrice.
  • Guelpa E., Sciacovelli A., Verda V., Thermo-fluid dynamic model of large district heating networks for the analysis of primary energy savings, Energy 2017, http://dx.doi.org/10.1016/j.energy.2017.07.177.
  • Guelpa E., Sciacovelli A., Verda V., Thermo-fluid dynamic model of complex district heating networks for the analysis of peak load reductions in the thermal plants, Proceedings of the ASME 2015.
  • Versteeg H. K., Malalasekera W., An introduction to computational fluid dynamics: The finite volume method, Pearson Education Limited, 2017.
Year 2019, , 35 - 43, 02.03.2019
https://doi.org/10.5541/ijot.519101

Abstract

References

  • Frederiksen S., Werner S., District heating and cooling, Lund Studentlitteratur, 2013.
  • Werner S., International review of district heating and cooling, Energy 2017;137:617631.
  • Sartor K., Thomas D., Dewallef P., A comparative study for simulating heat transport in large district heating networks, International Journal of Heat and Technology 2018;36:301-308.
  • Ancona M.A., Melino F., Peretto A., An optimization procedure for district heating networks, Energy procedia 2014;61:278-281.
  • Bojic M., Trifunovic N., Linear programming optimization of heat distribution in a district-heating system by valve adjustments and substation retrofit, Building and Environment 2000;35:151-159.
  • Koiv T.A., Mikola A., Palmiste U., The new dimensioning method of the district heating network, Applied Thermal Energy 2014;71(1):78-82.
  • Wang H., Yin W., Zhou Z., Lahdelma R., Optimizing the design of a district heating network, Proceedings of ECOS 2015, Pau, France, June 30-July 31.
  • Guelpa E., Mutani G., Todeschi V., Verda V., Reduction of CO2 emissions in urban areas through optimal expansion of existing district heating networks Journal of Cleaner Production 2018;204:117-129.
  • Giraud L., Baviere R., Vallee M., Paulus C., Presentation, validation and application of the DistrictHeating Modelica library, Proceedings of the 11th International Modelica Conference 2015, Versailles, France, September 21-23.
  • Pirouti M., Bagdanavicius A., Wu J., Ekanayake J., Optimization of supply temperature and mass flow rate for a district heating network, Proceedings of ECOS 2012, Perugia, Italy, June 26-29.
  • Lindenberger D., Bruckner T., Groscurth H.M., Kummel R.,¨ Optimization of solar district heating systems: seasonal storage, heat pumps, and cogeneration, Energy 2000;25(7):591-608.
  • Verda V., Colella F., Primary energy savings through thermal storage in district heating networks, Energy 2011;36(7):4278-4286.
  • Guelpa E., Verda V., Optimization of the thermal load profile in district heating networks through “virtual storage” at building level Energy procedia 2016;101:798805.
  • Guelpa, E., Marincioni, L., & Verda, V. (2019). Towards 4th generation district heating: Prediction of building thermal load for optimal management. Energy.
  • Verda V., Guelpa E., Sciacovelli A., Acquaviva A., Patti E., Thermal peak load shaving through users request variations in district heating systems, International Journal of Thermodynamics 2016;19(3):168-176.
  • Guelpa E., Barbero G., Sciacovelli A., Verda V., Peak-shaving in district heating systems through optimal management of the thermal request of buildings, Energy 2017;137:706-714.
  • Guelpa E., Deputato S., Verda V., Thermal request optimization in district heating networks using a clustering approach, Applied Energy 2018;228:608-617.
  • Del Hoyo Arce I., Herrero Lopez S., L´ opez Perez S., R´ am¨ a M., Klobut K., Febres J. A.,¨ Models for fast modelling of district heating and cooling networks, Renewable and Sustainable Energy Reviews 2018;82:1863-1873.
  • Harary F., Graph theory, New Delhi: Narosa Publishing House, 1995.
  • Sciacovelli A., Verda V., Borchiellini R., Numerical design of thermal systems, 2015, CLUT Editrice.
  • Guelpa E., Sciacovelli A., Verda V., Thermo-fluid dynamic model of large district heating networks for the analysis of primary energy savings, Energy 2017, http://dx.doi.org/10.1016/j.energy.2017.07.177.
  • Guelpa E., Sciacovelli A., Verda V., Thermo-fluid dynamic model of complex district heating networks for the analysis of peak load reductions in the thermal plants, Proceedings of the ASME 2015.
  • Versteeg H. K., Malalasekera W., An introduction to computational fluid dynamics: The finite volume method, Pearson Education Limited, 2017.
There are 23 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Regular Original Research Article
Authors

Vittorio Verda

Martina Capone This is me

Elisa Guelpa

Publication Date March 2, 2019
Published in Issue Year 2019

Cite

APA Verda, V., Capone, M., & Guelpa, E. (2019). Optimal operation of district heating networks through demand response. International Journal of Thermodynamics, 22(1), 35-43. https://doi.org/10.5541/ijot.519101
AMA Verda V, Capone M, Guelpa E. Optimal operation of district heating networks through demand response. International Journal of Thermodynamics. March 2019;22(1):35-43. doi:10.5541/ijot.519101
Chicago Verda, Vittorio, Martina Capone, and Elisa Guelpa. “Optimal Operation of District Heating Networks through Demand Response”. International Journal of Thermodynamics 22, no. 1 (March 2019): 35-43. https://doi.org/10.5541/ijot.519101.
EndNote Verda V, Capone M, Guelpa E (March 1, 2019) Optimal operation of district heating networks through demand response. International Journal of Thermodynamics 22 1 35–43.
IEEE V. Verda, M. Capone, and E. Guelpa, “Optimal operation of district heating networks through demand response”, International Journal of Thermodynamics, vol. 22, no. 1, pp. 35–43, 2019, doi: 10.5541/ijot.519101.
ISNAD Verda, Vittorio et al. “Optimal Operation of District Heating Networks through Demand Response”. International Journal of Thermodynamics 22/1 (March 2019), 35-43. https://doi.org/10.5541/ijot.519101.
JAMA Verda V, Capone M, Guelpa E. Optimal operation of district heating networks through demand response. International Journal of Thermodynamics. 2019;22:35–43.
MLA Verda, Vittorio et al. “Optimal Operation of District Heating Networks through Demand Response”. International Journal of Thermodynamics, vol. 22, no. 1, 2019, pp. 35-43, doi:10.5541/ijot.519101.
Vancouver Verda V, Capone M, Guelpa E. Optimal operation of district heating networks through demand response. International Journal of Thermodynamics. 2019;22(1):35-43.

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