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

Building energy simulation (BES) has been widely adopted for the investigation of building environmen-tal 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 philos-ophy, 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. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Building energy simulation (BES) and data-driven analytics are currently not seamlessly integrated, but the eplusr R package offers a more convenient way to conduct data-driven analytics to reveal trends and provide useful insights.