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Title: eplusr: A framework for integrating building energy simulation and data-driven analytics
Authors: Jia, H
Chong, A 
Issue Date: 15-Apr-2021
Publisher: Elsevier BV
Citation: Jia, H, Chong, A (2021-04-15). eplusr: A framework for integrating building energy simulation and data-driven analytics. Energy and Buildings 237 : 110757-110757. ScholarBank@NUS Repository.
Abstract: 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.
Source Title: Energy and Buildings
ISSN: 03787788
DOI: 10.1016/j.enbuild.2021.110757
Appears in Collections:Staff Publications

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