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

被引:14
|
作者
Jia, Hongyuan [1 ]
Chong, Adrian [2 ]
机构
[1] Berkeley Educ Alliance Res Singapore, SinBerBEST Program, Singapore 138602, Singapore
[2] Natl Univ Singapore, Sch Design & Environm, Dept Bldg, 4 Architecture Dr, Singapore 117566, Singapore
基金
新加坡国家研究基金会;
关键词
EnergyPlus; Building performance simulation; Building energy simulation; Datadriven analytics; Parametric simulation; Bayesian calibration; Optimization; R; BAYESIAN CALIBRATION; GENERATION; MANAGEMENT; MODELS;
D O I
10.1016/j.enbuild.2021.110757
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:28
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