An open source analysis framework for large-scale building energy modeling. Issue 5 (2nd September 2020)

• Record Type: Journal Article
• Authors: Ball, Brian L.; Long, Nicholas; Fleming, Katherine; Balbach, Chris; Lopez, Phylroy
• Is Part Of: Journal of building performance simulation. Volume 13:Issue 5(2020)
• Page Start: 487
• Page End: 500
• Publication Date: 2020-09-02
• Subjects: Parametric analysis -- optimization -- calibration -- sensitivity analysis -- uncertainty quantification -- OpenStudio Analysis Framework; 690.0113
• DOI: 10.1080/19401493.2020.1778788
• Languages: English
• ISSNs: 1940-1493

Abstract

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.