An open source analysis framework for large-scale building energy modeling

被引:4
|
作者
Ball, Brian L. [1 ]
Long, Nicholas [1 ]
Fleming, Katherine [1 ]
Balbach, Chris [2 ]
Lopez, Phylroy [3 ]
机构
[1] Natl Renewable Energy Lab, 15013 Denver West Pkwy, Golden, CO 80401 USA
[2] Performance Syst Dev, Ithaca, NY USA
[3] Nat Resources Canada, Ottawa, ON, Canada
关键词
Parametric analysis; optimization; calibration; sensitivity analysis; uncertainty quantification; OpenStudio Analysis Framework; SENSITIVITY-ANALYSIS METHODS; OPTIMIZATION TOOLS; PACKAGE; CALIBRATION; UNCERTAINTY; ALGORITHM; DESIGN; GA;
D O I
10.1080/19401493.2020.1778788
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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 (R) 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.
引用
收藏
页码:487 / 500
页数:14
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