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Linking energy efficiency policies toward 4th generation district heating system

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  • Pakere, Ieva
  • Gravelsins, Armands
  • Lauka, Dace
  • Bazbauers, Gatis
  • Blumberga, Dagnija

Abstract

Implementation of 4th or 5th generation district heating system needs a complex solution as it involves an energy source, a heating network and consumers. Retrofitting of buildings and energy efficiency level have been the main factors defining an implementation of the low temperature heat solutions. When evaluating the national heat supply system, it is difficult to evaluate the readiness of buildings to accept lower temperature heat carriers. Therefore, the system dynamics modelling approach has been used to determine the links between different elements of 4th generation district heating system in the long-term perspective. The developed system dynamic model allows evaluating whether the allocated financial support is sufficient for reaching the set energy efficiency goals, as well as to achieve the desired performance of district heating systems. The study analysed various policy measures and their long-term effects. The modelling results show that support in the form of subsidies has a greater impact on key targets than tax increases. In the combined policy scenario with increased fossil fuel tax and subsidies for RES technologies it is possible to achieve the share of RES up to 80% in DH and 62% in individual heat supply.

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  • Pakere, Ieva & Gravelsins, Armands & Lauka, Dace & Bazbauers, Gatis & Blumberga, Dagnija, 2021. "Linking energy efficiency policies toward 4th generation district heating system," Energy, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:energy:v:234:y:2021:i:c:s0360544221014936
    DOI: 10.1016/j.energy.2021.121245
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    5. Madurai Elavarasan, Rajvikram & Pugazhendhi, Rishi & Irfan, Muhammad & Mihet-Popa, Lucian & Khan, Irfan Ahmad & Campana, Pietro Elia, 2022. "State-of-the-art sustainable approaches for deeper decarbonization in Europe – An endowment to climate neutral vision," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    6. Yuan, Jianjuan & Huang, Ke & Han, Zhao & Wang, Chendong & Lu, Shilei & Zhou, Zhihua, 2022. "Evaluation of the operation data for improving the prediction accuracy of heating parameters in heating substation," Energy, Elsevier, vol. 238(PB).
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    8. Ziemele, Jelena & Dace, Elina, 2022. "An analytical framework for assessing the integration of the waste heat into a district heating system: Case of the city of Riga," Energy, Elsevier, vol. 254(PB).

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