An Open Source Analysis Framework for Large-Scale Building Energy Modeling

Brian Ball, Nicholas Long, Katherine Fleming, Chris Balbach, Phylroy Lopez

Research output: Contribution to journalArticlepeer-review

10 Scopus Citations

Abstract

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

Original languageAmerican English
Pages (from-to)487-500
Number of pages14
JournalJournal of Building Performance Simulation
Volume13
Issue number5
DOIs
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020, © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

NREL Publication Number

  • NREL/JA-5500-76261

Keywords

  • calibration
  • OpenStudio Analysis Framework
  • optimization
  • Parametric analysis
  • sensitivity analysis
  • uncertainty quantification

Fingerprint

Dive into the research topics of 'An Open Source Analysis Framework for Large-Scale Building Energy Modeling'. Together they form a unique fingerprint.

Cite this