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Data-driven building archetypes for urban building energy modelling
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Resources, Energy and Infrastructure.ORCID iD: 0000-0001-5550-1601
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Applied Thermodynamics and Refrigeration.ORCID iD: 0000-0003-3194-1762
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Resources, Energy and Infrastructure.ORCID iD: 0000-0002-4830-7832
2019 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 181, p. 360-377Article in journal (Refereed) Published
Abstract [en]

This paper presents an approach for using rich datasets to develop different building archetypes depending on the urban energy challenges addressed. Two cases (building retrofitting and electric heating) were analysed using the same city, Stockholm (Sweden), and the same input data, energy performance certificates and heat energy use metering data. The distinctive character of these problems resulted in different modelling workflows and archetypes being developed. The building retrofitting case followed a hybrid approach, integrating statistical and physical perspectives, estimating energy savings for 5532 buildings from seven retrofitting packages. The electric heating case provided an explicitly statistical data-driven view of the problem, estimating potential for improvement of power capacity of the local electric grid at peak electric power of 147 MW. The conclusion was that the growing availability of linked building energy data requires a shift in the urban building energy modelling (UBEM) paradigm from single-logic models to on-request multiple-purpose data intelligence services.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 181, p. 360-377
Keywords [en]
Building archetype, Urban building energy modelling, Building retrofitting, Electric heating, Stockholm
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-255724DOI: 10.1016/j.energy.2019.04.197ISI: 000476965900030Scopus ID: 2-s2.0-85067083111OAI: oai:DiVA.org:kth-255724DiVA, id: diva2:1342350
Conference
10th Biennial International Workshop on Advances in Energy Studies IWAES), SEP 25-28, 2017, Naples, ITALY
Note

QC 20190813

Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-12-20Bibliographically approved

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Pasichnyi, OleksiiWallin, JörgenKordas, Olga

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