Energy Benchmarking in Educational Buildings through Cluster Analysis of Energy Retrofitting

Paola Marrone, Paola Gori, Francesco Asdrubali, Luca Evangelisti, Laura Calcagnini and Gianluca Grazieschi
Additional contact information
Paola Marrone: Department of Architecture, Roma TRE University, Via della Madonna dei Monti 40, 00184 Rome, Italy
Paola Gori: Department of Engineering, Roma TRE University, Via Vito Volterra 62, 00146 Rome, Italy
Francesco Asdrubali: Department of Engineering, Roma TRE University, Via Vito Volterra 62, 00146 Rome, Italy
Luca Evangelisti: Department of Engineering, Roma TRE University, Via Vito Volterra 62, 00146 Rome, Italy
Laura Calcagnini: Department of Architecture, Roma TRE University, Via della Madonna dei Monti 40, 00184 Rome, Italy
Gianluca Grazieschi: Department of Engineering, Niccolò Cusano University, Via don Carlo Gnocchi 3, 00166 Rome, Italy

Energies, 2018, vol. 11, issue 3, 1-20

Abstract: A large part of the stock of Italian educational buildings have undertaken energy retrofit interventions, thanks to European funds allocated by complex technical-administrative calls. In these projects, the suggested retrofit strategies are often selected based on the common best practices (considering average energy savings) but are not supported by proper energy investigations. In this paper, Italian school buildings’ stock was analyzed by cluster analysis with the aim of providing a methodology able to identify the best energy retrofit interventions from the perspective of cost-benefit, and to correlate them with the specific characteristics of the educational buildings. This research is based on the analysis of about 80 school buildings located in central Italy and characterized by different features and construction technologies. The refurbished buildings were classified in homogeneous clusters and, for each of them, the most representative building was identified. Furthermore, for each representative building a validating procedure based on dynamic simulations and a comparison with actual energy use was performed. The two buildings thus singled out provide a model that could be developed into a useful tool for Public Administrations to suggest priorities in the planning of new energy retrofits of existing school building stocks.

Keywords: cluster analysis; school buildings; energy efficiency; cost-effectiveness; retrofit interventions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/3/649/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/3/649/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:3:p:649-:d:136272

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().