A Functional Data Analysis for Assessing the Impact of a Retrofitting in the Energy Performance of a Building

Miguel Martínez Comesaña, Sandra Martínez Mariño, Pablo Eguía Oller, Enrique Granada Álvarez and Aitor Erkoreka González
Additional contact information
Miguel Martínez Comesaña: Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, Industrial Engineering School, University of Vigo, Maxwell s/n, 36310 Vigo, Spain
Sandra Martínez Mariño: Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, Industrial Engineering School, University of Vigo, Maxwell s/n, 36310 Vigo, Spain
Pablo Eguía Oller: Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, Industrial Engineering School, University of Vigo, Maxwell s/n, 36310 Vigo, Spain
Enrique Granada Álvarez: Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, Industrial Engineering School, University of Vigo, Maxwell s/n, 36310 Vigo, Spain
Aitor Erkoreka González: ENEDI Research Group, Department of Thermal Engineering, University of the Basque Country, 48013 Bilbao, Spain

Mathematics, 2020, vol. 8, issue 4, 1-20

Abstract: There is an increasing interest in reducing the energy consumption in buildings and in improving their energy efficiency. Building retrofitting is the employed solution for enhancing the energy efficiency in existing buildings. However, the actual performance after retrofitting should be analysed to check the effectiveness of the energy conservation measures. The aim of this work was to detect and to quantify the impact that a retrofitting had in the electrical consumption, heating demands, lighting and temperatures of a building located in the north of Spain. The methodology employed is the application of Functional Data Analyses (FDA) in comparison with classic mathematical techniques such as the Analysis of Variance (ANOVA). The methods that are commonly used for assessing building refurbishment are based on vectorial approaches. The novelty of this work is the application of FDA for assessing the energy performance of renovated buildings. The study proves that more accurate and realistic results are obtained working with correlated datasets than with independently distributed observations of classical methods. Moreover, the electrical savings reached values of more than 70% and the heating demands were reduced more than 15% for all floors in the building.

Keywords: retrofitting; refurbishment; functional data analysis; vectorial analysis; energy efficiency (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/4/547/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/4/547/ (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:jmathe:v:8:y:2020:i:4:p:547-:d:342600

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

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