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Evaluating Energy Performance Certificate Data with Data Science

2021-12-09Documento de conferência Acesso aberto
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dc.contributor.authorAnastasiadou, Maria
dc.contributor.authorSantos, Vitor
dc.contributor.authorDias, Miguel Sales
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.date.accessioned2022-02-15T23:14:56Z
dc.date.available2022-02-15T23:14:56Z
dc.date.issued2021-12-09
dc.descriptionAnastasiadou, M., Santos, V., & Dias, M. S. (2021). Evaluating Energy Performance Certificate Data with Data Science. In 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-5). IEEE. https://doi.org/10.1109/ICECET52533.2021.9698806
dc.description.abstractThe related problems of improving existing buildings' energy performance, reducing energy consumption, and improving indoor comfort and their many consequences are well known. Considering increasing urbanization and climate change, governments define strategies to enhance and measure buildings' energy performance and energy efficiency. This work aims to contribute to the improvement of buildings' characteristics by conducting a thorough systematic literature review and adopting a data science approach to these problems, presenting initial results with an open-access energy performance certificate dataset from the Lombardy Region, in Italy. We provide a pre-processing method to the data, applicable for future research, aiming to address challenges such as automatic classification of existing buildings' energy performance certification, and predicting energy-efficient retrofit measures, using machine learning techniques. The analysis of this dataset is challenging because of the high variability and dimensionality of this dataset. For this purpose, a robust iterative process was developed. First, the data dimensionality was reduced with Pearson Correlation to find the best set of variables against the non-renewable global energy performance index (EPgl, nren). Then, the outliers were handled by utilizing Box Plot and Isolation Forest algorithms. The main contribution is to inform private and public building sectors on dealing with high dimensional data to achieve enhanced energy performance and predict energy-efficient retrofit measures to improve their energy performance.en
dc.description.versionauthorsversion
dc.description.versionpublished
dc.format.extent5
dc.format.extent366777
dc.identifier.doi10.1109/ICECET52533.2021.9698806
dc.identifier.isbn978-1-6654-4232-9
dc.identifier.isbn978-1-6654-4231-2
dc.identifier.otherPURE: 41766389
dc.identifier.otherPURE UUID: f3d62c7f-4f12-4b83-a4b0-ef58c6a7372c
dc.identifier.othercrossref: 10.1109/ICECET52533.2021.9698806
dc.identifier.otherScopus: 85127037433
dc.identifier.otherWOS: 000814669100347
dc.identifier.otherORCID: /0000-0002-4223-7079/work/108281489
dc.identifier.urihttp://hdl.handle.net/10362/132938
dc.identifier.urlhttps://www.scopus.com/pages/publications/85127037433
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000814669100347
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9698806/
dc.language.isoeng
dc.peerreviewedyes
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectEnergy performance of buildings
dc.subjectEnergy performance certification
dc.subjectprediction of retrofitting measures
dc.subjectmachine learning
dc.subjectSystematics
dc.subjectData science
dc.subjectForestry
dc.subjectCorrelation
dc.subjectClustering algorithms
dc.subjectEnergy measurement
dc.subjectBuildings
dc.subjectElectrical and Electronic Engineering
dc.subjectGeneral Computer Science
dc.subjectEnergy Engineering and Power Technology
dc.subjectSDG 7 - Affordable and Clean Energy
dc.subjectSDG 13 - Climate Action
dc.titleEvaluating Energy Performance Certificate Data with Data Scienceen
dc.typeconference object
degois.publication.firstPage1
degois.publication.lastPage5
degois.publication.title2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)
degois.publication.title2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)
dspace.entity.typePublication
rcaap.rightsopenAccess

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NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)