Developing a Common Approach for Classifying Building Stock Energy Models

Jared Langevin, Janet Reyna, Shima Ebrahimigharenbaghi, Nina Sandberg, Pamela Fennell, Claudio Nägeli, Jelle Laverge, Marc Delghust, Erika Mata, Matthias Van Hove, Jessica Webster, Felicia Federico, Martin Jakob, Clara Camarasa

Research output: Contribution to journalArticlepeer-review

61 Scopus Citations

Abstract

Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

Original languageAmerican English
Article number110276
Number of pages15
JournalRenewable and Sustainable Energy Reviews
Volume133
DOIs
StatePublished - Nov 2020

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

NREL Publication Number

  • NREL/JA-5500-75689

Keywords

  • Building stock energy models
  • Energy epidemiology
  • IEA Annex 70
  • Model classification
  • Urban building energy modeling

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