Demonstration of Reduced-Order Urban Scale Building Energy Models

Kyle Benne, Mohammad Heidarinejad, Nicholas Mattise, Matthew Dahlhausen, Krishang Sharma, Jelena Srebric, Daniel Macumber, Larry Brackney

Research output: Contribution to journalArticlepeer-review

40 Scopus Citations


The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% with the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Overall, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.

Original languageAmerican English
Pages (from-to)17-28
Number of pages12
JournalEnergy and Buildings
StatePublished - 1 Dec 2017

Bibliographical note

Publisher Copyright:
© 2017 Elsevier B.V.

NREL Publication Number

  • NREL/JA-5500-70142


  • Building energy model
  • Calibration
  • OpenStudio
  • Reduced-order model
  • Typical building shapes


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