Abstract

Traditional energy modeling methods are usually time-consuming and labour-intensive, so energy simulation is rarely performed early in building design. If a Building Energy Model (BEM) can be seamlessly generated from a Building Information Modeling (BIM) model, the energy simulation process can be much more efficient and better integrated in design. The concerns about BIM to BEM data transfer integrity and the reliability of simulation results are preventing wider adoption of BIM-based energy simulation. This study aimed to address these two obstacles and increase energy modelers’ confidence in using BIM for energy analysis. Green Building Studio (GBS) was used to simulate energy use and generate eQuest and EnergyPlus input files. Two building types were modeled in Revit with various iterations and BEM input files downloaded from GBS were compared line by line to identify and classify discrepancies. Simulation results from BIM-based and traditional modeling were compared to test reliability and showed unexpectedly good agreement across methods.

Highlights

  • As one of the participating nations of UN Framework Convention on Climate Change (UNFCCC) Conference of the Parties (COP21), Canada has encouraged its provinces to establish greenhouse gas (GHG) reduction target and action plans

  • 2.4.3 Prevalent Building Energy Modeling (BEM) software and compatibility with Building Information Modeling (BIM) There are 133 BEM tools listed on Building Energy Simulation Tools web directory (BEST-D), which was hosted by the US Department of Energy (DOE) until late 2014 and is currently managed by International Building Performance Simulation Association (IBPSA-USA) (IBPSA 2016)

  • There are an increasing number of BIM-based energy analysis tools could have been considered, e.g. Revit IES plug-in, Revit DesignBuilder plug-in, or SketchUp OpenStudio (EnergyPlus) plug-in, but due to time limitations, only Green Building Studio (GBS) was investigated for the following three reasons: 1. GBS eliminates the challenge of software interoperability issues: o It is integrated within Autodesk Revit, which is the most widely-used BIM software across all disciplines; o It generates three BEM input files and offers the most flexibility in testing data transfer across platforms: (1) Green Building Extensible Markup Language (gbXML), which is used by an increasing number of BEM tools, (2) INP for eQuest, and (3) IDF for EnergyPlus

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Summary

INTRODUCTION

As one of the participating nations of UN Framework Convention on Climate Change (UNFCCC) Conference of the Parties (COP21), Canada has encouraged its provinces to establish greenhouse gas (GHG) reduction target and action plans. The lack of successful case studies showcasing energy modeling’s positive impacts (AIA 2015) is partially responsible for the insufficient adoption, but the considerable amount of time and effort demanded by energy modeling using the traditional method is a likely factor because it requires to re-create the geometry in a native BEM tool based on architectural drawings and define these properties in detail (Gane and Haymaker 2010) This is where BIM can improve the modeling efficiency because the BIM model already contains a good amount of information (e.g. geometry and construction) required by energy modeling and eliminates the time consuming and labour intensive remodeling process and facilitates repeated energy modeling as the design progresses (Ham and Golparvar-Fard 2015, Kim, et al 2015).

CONTEXT OF RESEARCH
BIM use cases
Disaster planning
The benefits of BIM-based energy analysis
Prevalent BIM tools There are a number of BIM tools on the market and
Prevalent intermediate formats and compatibility with BIM
Prevalent BEM software and compatibility with BIM
A lack of academic research support Wong and
BIM to BEM data transfer integrity assessment
Simulation results evaluation
Software and the interoperability
Procedural difficulties
CURRENT PRACTICE IN BUILDING ENERGY MODELING
Software used for energy analysis
Current workflow
Traditional energy modeling approach
Strategies to improve modeling efficiency, accuracy, and flexibility
Preferred energy modeling input format
Opinions on BIM-based energy analysis
Barriers to BIM-based energy analysis
The development of research objectives and methodology
CASE STUDY METHODOLOGY
Case study 1
Energy model preparation
Case study 2
Model construction
Energy model preparation When creating spaces and zones on the
DATA TRANSFER INTEGRITY EVALUATION
Climatic data
Geometric data
BIM and BEM file inspection
GBS-introduced discrepancies
Revit-exported gbXML missing one roof surface
Model simplicity and discussion
Construction and material data
Construction
Exterior wall construction layers
Door construction
Additional exterior wall construction
Thermal properties
Mechanical systems
Internal loads The internal loads in each file are presented in
Schedules Since
Schedule conflicts Among all schedules, the equipment schedule was most deceiving
Schedule assumption concerns Although defined as a “12/5 Facility” in
COMPARISON OF SIMULATED RESULTS
BIM-based energy analysis results
ITERATION TESTING FOR SOURCES OF ERROR
BIM model iteration testing: climatic data
BIM model iteration testing
MODEL RESILIENCY TO GEOMETRY ERRORS
Testing methodology
Comparison of different gap locations
Comparison of space resolutions
Comparison of different building types
Geometric error results comparison summary
CONCLUSIONS
Findings
10 RECOMMENDATIONS
Full Text
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