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|Title:||eplusr: A framework for integrating building energy simulation and data-driven analytics||Authors:||Jia, H
|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. https://doi.org/10.1016/j.enbuild.2021.110757||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||URI:||https://scholarbank.nus.edu.sg/handle/10635/191879||ISSN:||03787788||DOI:||10.1016/j.enbuild.2021.110757|
|Appears in Collections:||Staff Publications|
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