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eplusr: A framework for integrating building energy simulation and data-driven analytics.

Authors :
Jia, Hongyuan
Chong, Adrian
Source :
Energy & Buildings. Apr2021, Vol. 237, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

[Display omitted] • Developed an R package that integrates EnergyPlus with data-driven analytics. • Structured inputs/outputs format that can be easily piped into data analytics workflows. • Facilitates reproducible simulations through Docker. • Enables flexible and extensible parametric simulations. Building energy simulation (BES) has been widely adopted for the investigation of building environmental and energy performance for different design and retrofit alternatives. Data-driven analytics is vital for interpreting and analyzing BES results to reveal trends and provide useful insights. However, seamless integration between BES and data-driven analytics current does not exist. This paper presents eplusr, an R package for conducting data-driven analytics with EnergyPlus. The R package is cross-platform and distributed using CRAN (The Comprehensive R Archive Network). With a data-centric design philosophy, the proposed framework focuses on better and more seamless integration between BES and data-driven analytics. It provides structured inputs/outputs format that can be easily piped into data analytics workflows. The R package also provides an infrastructure to bring portable and reusable computational environment for building energy modeling to facilitate reproducibility research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03787788
Volume :
237
Database :
Academic Search Index
Journal :
Energy & Buildings
Publication Type :
Academic Journal
Accession number :
149364890
Full Text :
https://doi.org/10.1016/j.enbuild.2021.110757