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On the classification of large residential buildings stocks by sample typologies for energy planning purposes

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  • Filogamo, Luana
  • Peri, Giorgia
  • Rizzo, Gianfranco
  • Giaccone, Antonino

Abstract

Local and central administrations are often called to properly allocate economic resources intended for the territorial energy planning, on the basis of the performances achieved by implementing energy conservation measures. Particularly in the residential sector, that represents one of the most relevant sector for the energy demand, effective and reliable evaluation tools are required for this aim. Unfortunately, building stocks are characterized by a very large number of buildings that are referred to different construction periods and are equipped with a variety of appliances and tools, other than with different heating and cooling systems. This means that the whole energy consumption of a large territorial context cannot be obtained by simply summing up the energy requirements of each single dwelling and building. A procedure is therefore needed that, by means of a suitable characterization of the building stock and of the structure of the energy consumption, allows to assess the whole residential energy requirements and the effects induced by energy conservation measures.

Suggested Citation

  • Filogamo, Luana & Peri, Giorgia & Rizzo, Gianfranco & Giaccone, Antonino, 2014. "On the classification of large residential buildings stocks by sample typologies for energy planning purposes," Applied Energy, Elsevier, vol. 135(C), pages 825-835.
    • Handle: RePEc:eee:appene:v:135:y:2014:i:c:p:825-835
    DOI: 10.1016/j.apenergy.2014.04.002
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    15. Younghoon Kwak & Jeonga Kang & Sun-Hye Mun & Young-Sun Jeong & Jung-Ho Huh, 2020. "Development and Application of a Flexible Modeling Approach to Reference Buildings for Energy Analysis," Energies, MDPI, vol. 13(21), pages 1-22, November.
    16. Talebi, Behrang & Haghighat, Fariborz & Tuohy, Paul & Mirzaei, Parham A., 2018. "Validation of a community district energy system model using field measured data," Energy, Elsevier, vol. 144(C), pages 694-706.
    17. Ilaria Ballarini & Vincenzo Corrado, 2017. "A New Methodology for Assessing the Energy Consumption of Building Stocks," Energies, MDPI, vol. 10(8), pages 1-22, July.
    18. Wang, Wei & Hong, Tianzhen & Xu, Xiaodong & Chen, Jiayu & Liu, Ziang & Xu, Ning, 2019. "Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm," Applied Energy, Elsevier, vol. 248(C), pages 217-230.
    19. Hargreaves, Anthony & Cheng, Vicky & Deshmukh, Sandip & Leach, Matthew & Steemers, Koen, 2017. "Forecasting how residential urban form affects the regional carbon savings and costs of retrofitting and decentralized energy supply," Applied Energy, Elsevier, vol. 186(P3), pages 549-561.
    20. Salata, Ferdinando & Golasi, Iacopo & di Salvatore, Maicol & de Lieto Vollaro, Andrea, 2016. "Energy and reliability optimization of a system that combines daylighting and artificial sources. A case study carried out in academic buildings," Applied Energy, Elsevier, vol. 169(C), pages 250-266.
    21. Sara Verones, 2017. "Retrofitting the existing building stock through a development rights market stimulation tool: An assessment of a recent experience in Northern Italy," Urban Studies, Urban Studies Journal Limited, vol. 54(8), pages 1905-1920, June.
    22. Aline Schaefer & Taylana Piccinini Scolaro & Enedir Ghisi, 2023. "Finding Patterns of Construction Systems in Low-Income Housing for Thermal and Energy Performance Evaluation through Cluster Analysis," Sustainability, MDPI, vol. 15(17), pages 1-23, August.
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    24. Hanan Ibrahim & Ahmed Z. Khan & Shady Attia & Yehya Serag, 2021. "Classification of heritage residential building stock and defining sustainable retrofitting scenarios in Khedivial Cairo," ULB Institutional Repository 2013/326195, ULB -- Universite Libre de Bruxelles.
    25. Francesco Calise & Mário Costa & Qiuwang Wang & Xiliang Zhang & Neven Duić, 2018. "Recent Advances in the Analysis of Sustainable Energy Systems," Energies, MDPI, vol. 11(10), pages 1-30, September.

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