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Guidelines for Using Building Information Modeling for Energy Analysis of Buildings

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Building energy modeling (BEM), a subset of building information modeling (BIM), integrates energy analysis into the design, construction, and operation and maintenance of buildings. As there are various existing BEM tools available, there is a need to evaluate the utility of these tools in various phases of the building lifecycle. The goal of this research was to develop guidelines for evaluation and selection of BEM tools to be used in particular building lifecycle phases. The objectives of this research were to: (1) Evaluate existing BEM tools; (2) Illustrate the application of the three BEM tools; (3) Re-evaluate the three BEM tools; and (4) Develop guidelines for evaluation, selection and application of BEM tools in the design, construction and operation/maintenance phases of buildings. Twelve BEM tools were initially evaluated using four criteria: interoperability, usability, available inputs, and available outputs. Each of the top three BEM tools selected based on this initial evaluation was used in a case study to simulate and evaluate energy usage, daylighting performance, and natural ventilation for two academic buildings (LEED-certified and non-LEED-certified). The results of the case study were used to re-evaluate the three BEM tools using the initial criteria with addition of the two new criteria (speed and accuracy), and to develop guidelines for evaluating and selecting BEM tools to analyze building energy performance. The major contribution of this research is the development of these guidelines that can help potential BEM users to identify the most appropriate BEM tool for application in particular building lifecycle phases.
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Buildings 2015, 5, 1361-1388; doi:10.3390/buildings5041361
buildings
ISSN 2075-5309
www.mdpi.com/journal/buildings/
Article
Guidelines for Using Building Information Modeling for Energy
Analysis of Buildings
Thomas Reeves 1,†, Svetlana Olbina 2,* and Raja R. A. Issa 3,†
1 FXFOWLE Architects, 22 W 19 Street, New York, NY 10011, USA;
E-Mail: treeves@fxfowle.com
2 Department of Construction Management, Colorado State University, 224A Guggenheim Hall,
Fort Collins, CO 80523, USA
3 Rinker School of Construction Management, University of Florida, 304 Rinker Hall, Gainesville,
FL 32611, USA; E-Mail: raymond-issa@ufl.edu
These authors contributed equally to this work.
* Author to whom correspondence should be addressed; E-Mail: svetlanaolbina@gmail.com;
Tel.: +1-970-491-7026.
Academic Editor: Tanyel Bulbul
Received: 23 June 2015 / Accepted: 1 December 2015 / Published: 9 December 2015
Abstract: Building energy modeling (BEM), a subset of building information modeling (BIM),
integrates energy analysis into the design, construction, and operation and maintenance of
buildings. As there are various existing BEM tools available, there is a need to evaluate the
utility of these tools in various phases of the building lifecycle. The goal of this research was
to develop guidelines for evaluation and selection of BEM tools to be used in particular
building lifecycle phases. The objectives of this research were to: (1) Evaluate existing BEM
tools; (2) Illustrate the application of the three BEM tools; (3) Re-evaluate the three BEM
tools; and (4) Develop guidelines for evaluation, selection and application of BEM tools in
the design, construction and operation/maintenance phases of buildings. Twelve BEM tools
were initially evaluated using four criteria: interoperability, usability, available inputs, and
available outputs. Each of the top three BEM tools selected based on this initial evaluation
was used in a case study to simulate and evaluate energy usage, daylighting performance, and
natural ventilation for two academic buildings (LEED-certified and non-LEED-certified).
The results of the case study were used to re-evaluate the three BEM tools using the initial
criteria with addition of the two new criteria (speed and accuracy), and to develop guidelines
for evaluating and selecting BEM tools to analyze building energy performance. The major
OPEN ACCESS
Buildings 2015, 5 1362
contribution of this research is the development of these guidelines that can help potential
BEM users to identify the most appropriate BEM tool for application in particular building
lifecycle phases.
Keywords: building information modeling (BIM); building energy modeling (BEM);
simulation; energy consumption; daylighting; natural ventilation
1. Introduction
As sustainability increasingly becomes a standard practice in the building industry, the demand for
high-performance buildings also increases [1]. Goals related to sustainability are being set ever higher,
demanding greater levels of energy and resource efficiency [2–4]. With the demand for high-performance
buildings and the resulting challenges posed to designers, builders and facility managers, the integration
of building performance analysis into the design, construction, and operation and maintenance of
buildings becomes crucial [2,5–8]. According to the US GSA [8] use of the building information
modeling (BIM)-based energy modeling provides several benefits including: more accurate and
complete energy performance analysis in early design stages, improved lifecycle cost analysis, and more
opportunities for monitoring actual building performance during the operation phase. Building
information modeling (BIM) in conjunction with building energy modeling (BEM) seeks to make this
integration seamless throughout the design process [8,9]. In addition, during the building operation and
maintenance phase, BEM can be used to improve energy efficiency through adjustments to system
operations and building retrofits [8].
The American Institute of Architects (AIA) [5] recognized the various benefits of using
BEM to the stakeholders involved in energy-efficient building projects. BEM helps designers create
energy-efficient buildings using a performance-based approach. Performance-based modeling provides
buildings owners with reduced life-cycle cost for the project (e.g., reduced initial cost, change orders,
operation and maintenance costs) while building occupants experience higher level of comfort and
consequently higher satisfaction with their indoor environment.
Design of energy efficient buildings requires validation of building performance which is typically
completed using building simulation software [7]. In addition, designing energy-efficient buildings is
not intuitive [2] and interactions among various parameters of these buildings are best studied using
BEM tools [6]. According to Bambardekar and Poerschke [10], there is very limited guidance to
architects for understanding and integrating BEM in the design process. In addition, they noted that
selection of BEM tools is not a trivial task and that it requires better guidance [10]. Architects have a
limited background in energy simulation and often do not understand how to translate design concepts
into BEM tools [2,10]. They prefer using intuition and rule of thumb approaches rather than using BEM [10].
As there are several existing BEM tools available, there is a need to evaluate how these various tools
can be used within the architecture, engineering, construction, and operation and maintenance (AECOM)
industry [8,10–12]. There is also a need to provide a guide for selection of the appropriate BEM tool to
facilitate energy simulations [10]. Therefore, the goal of this research was to develop guidelines for
evaluation, selection and application of BEM for the energy analysis of buildings in the various lifecycle
Buildings 2015, 5 1363
phases (design, construction, and operation/maintenance). In particular, the research focused on whole
building energy use, daylighting, and natural ventilation potential. Intended users of the guidelines are
building designers, green building consultants, contractors, and facility managers. The research
objectives were to:
(1) Evaluate major existing BEM software tools.
(2) Illustrate the application of the three BEM tools selected based on the initial evaluation.
(3) Re-evaluate the three BEM tools using an updated set of criteria.
(4) Develop a set of guidelines to help potential BEM users evaluate, select and use the most
appropriate BEM tool.
The major contribution of this research is the development of guidelines for the evaluation and
selection of BEM tools relative to application and usability of the tools in various phases of the building
lifecycle. As discussed earlier, previous research identified the need for the development of such
guidelines as there are many BEM tools available and typical project stakeholders (architects,
contractors, facility managers) find it challenging to use some of these BEM tools.
2. Literature Review
BEM may be utilized in various phases of the building lifecycle to improve building energy
performance [4,13]. In the design phase, design professionals can use BEM simulations to analyze the
energy performance of various design alternatives in order to select the most efficient
design [6,8,9,14,15]. In the construction phase, BEM is used mostly to assess different alternatives that
are created due to change orders [6,8]. In the building operation phase, BEM can be used to predict
actual building performance [8,16]. Use of BEM to predict actual energy consumption during building
operation requires calibrating the building energy model to be as close as possible to how the building
will actually be built, occupied and operated [17]. In either case, BEM can be used as a decision support
tool that simulates building performance under idealized conditions [18] or under realistic conditions [14].
Idealized conditions focus primarily on parameters like building geometry, structure, materials, and
HVAC, and do not include real-life parameters such as building occupant behavior. On the other hand,
realistic conditions consider building occupant behavior for which information can be gathered by using
actual measured data or by conducting surveys of building occupants [14,19,20].
The level of detail of an energy model and depth of energy analysis depend on the building lifecycle
phase [8]. For example, in the conceptual design phase simple models and quick analysis are
sufficient [11] while in the design development and construction documents phase more detailed models
and in-depth energy analysis are necessary [8]. In the construction phase, a detail model is used to
conduct a comprehensive evaluation of the effect of change orders and construction detailing. The
detailed model is also required in the building operation phase in order to conduct in-depth analysis of
the building’s actual energy performance [8].
2.1. BIM and BEM
The emergence of BIM in the building industry has allowed for increased collaboration among
building design and construction project members [13,15,21,22]. In the traditional project delivery
Buildings 2015, 5 1364
method, the work of architects, structural engineers, MEP engineers, contractors, and various other
building consultants occurs in relative isolation to one another. However, BIM-based project delivery
facilitates collaboration among the project stakeholders [13,15,21,22]. In this case, information available
to the various parties can all be shared and integrated around a central building information model [1].
In addition, immersive virtual environments (IVEs) combine pre-construction mock-up that presents
a sense of real space to the future users and building information models that allow for testing of different
design alternatives [22,23]. Use of IVEs provides designers and engineers with the opportunity to collect
information about occupant behavior [22]. This information can be very helpful for making decisions
during the project design phase.
According to the US GSA [8], in the case of a traditional energy modeling approach, an energy
modeler uses traditionally created drawings and creates an independent model in an energy modeling
tool. This may lead to misinterpretation of the drawings, inconsistencies, simplified model, and large
amount of time needed to create an energy model. On the other hand, BIM-based energy modeling helps
automate this process, and create consistent and more complex energy models [8]. In BIM-based project
delivery, BEM is integrated into building design, construction, and operation/maintenance more
efficiently because energy performance is analyzed using the central BIM model without having to
recreate building geometry in certain BEM platforms (i.e., gbXML-enabled BEM tools). In addition,
BIM-based sustainability analysis provides the results faster as compared to the traditional methods [1].
Although there is a need for higher levels of interoperability between BIM and BEM tools [24], the
efficiency and accuracy of BIM-based energy modeling is constantly improving [9].
2.2. Use of BEM in the Building Design Phase
Many of the most important decisions related to energy efficiency are made early on in the design
process [4,9,12,15,25]. The earlier BEM simulations are performed in the design process the more
energy savings can be achieved later on in the project [7]. Therefore, the use of BEM tools can be very
beneficial during the design phase [2,10,15,24]. BEM simulations can be used to assess the energy
benefits of various design alternatives and thus help designers and owners make better decisions related
to building performance [8,12] and lifecycle cost benefits [26]. Building designers use BEM as a design
tool to analyze the performance of building design iterations through BEM simulations [12]. In the
design phase a need for the qualitative comparison of design alternatives is more important than accuracy
of simulation results [2,10]. The Chartered Institution of Building Service Engineers (CIBSE) [27]
proposed two methods for integrating BEM in design: (1) applying simplified simulation tools in the
early design phase and more detailed tools in the detailed design phases, and (2) using a sophisticated
single simulation tool in all the design phases. The advantage of the second method is that with the use
of the single tool the same building energy model is used by different team members in all the design
phases. This approach also eliminates errors that may occur due to use of different BEM tools [28].
Similarly, Hemsath [7] suggested using multiple BEM tools throughout the design process depending
on the design phase and the scope of simulation.
BEM can help designers achieve sustainable buildings by providing tools that can be used for energy
analysis, selecting materials and products that have low environmental impact, and evaluating projects
for LEED compliance [21]. Stadel et al. [26] showed how certain BIM platforms (e.g., Revit) that are
Buildings 2015, 5 1365
able to quickly perform quantity takeoffs can be used in connection with certain BEM software (e.g.,
Green Building Studio™ Revit Plugin, IES VE™ Revit Plugin, and SimaPro). These software tools can
be used for performing lifecycle analysis in order to estimate the environmental impact (in terms of
lifecycle energy consumption and greenhouse gas emissions) of building materials from the cradle to
grave phases.
Effective use of BEM can span from the conceptual design phase [2,5,12], through the design
development and the construction documents phase [8]. In the preliminary conceptual design phase, the
BEM model is typically used for evaluating the impact of building location and orientation, building
massing, and building envelope while in the final conceptual design phase alternative designs are
compared in regard to the various building layouts, building component structures and HVAC
systems [5–8]. More detail energy performance analysis is conducted in the design development phase
by using BEM to evaluate the effect of different building systems and subsystems such as windows,
insulations, and control systems [5–7]. In the final construction document phase, additional BEM
analysis is performed to make sure that the building design meets all the required energy codes and, if
desired, green building certification requirements [5–8].
Donn et al. [12] illustrated the effective implementation of BEM simulations in the early stages of
the design process using the building performance sketch approach. The goal of their research was to
assess the use of detailed simulation tools during early design stages when there is greater freedom to
explore various design concepts and greater ability to improve building performance. The two main
criteria that Donn et al. [12] used for determining a high quality simulation tool were speed and accuracy.
Evaluating the speed of a simulation tool is necessary in order to provide feedback quickly enough to
keep up with the rapid pace of the design sketch process. Accuracy is necessary to ensure that the results
are reliable [14] and the subsequent design decisions are effective [12]. The building performance sketch
was compared to the BIM-based simulation workflow in which a relatively complete, whole-building
information model is first finalized and then design iterations are analyzed based on feedback from the
simulation tool [12]. The BIM-based workflow requires that the building design is relatively complete [1].
Another limitation of the BIM-based workflow is that by the time the design is ready for energy analysis,
many of the design decisions that carry the greatest weight in regard to overall energy consumption have
already been made and fewer design changes are possible [15].
Heydarian et al. [19] found that bringing real world human data from the physical world into the
simulation model is a challenge for building designers. According to Heydarian et al. [19] the use of
virtual reality technologies can help building designers evaluate different design alternatives. Thus,
Heydarian et al. [19] used an immersive virtual environment (IVE) to create different design alternatives
and to provide realistic representation of the physical environment. The building occupant input was
incorporated in these IVE models by allowing occupants to control lighting settings.
Attia et al. [2] noted that architects found it difficult to integrate existing BEM tools into design of
zero-energy buildings. At the same time, Attia et al. [2] understood the importance of including building
performance evaluation in the early design stages of zero-energy buildings. In addition, they noted that
no existing BEM tool was applicable to the design of zero-energy buildings. Therefore, Attia et al. [2]
developed an energy software tool that provided support for decision making in the early design of
zero-energy buildings. This tool could assist architects in making decision about building parameters
that would help achieve zero-energy building as well as perform sensitivity analysis of these parameters.
Buildings 2015, 5 1366
2.3. Use of BEM in the Building Construction Phase
For building constructors, use of BEM is especially beneficial on projects that must meet certain
performance requirements [21]. During the construction phase, BEM can be used to analyze data related
to heating and cooling loads in order to determine the size of the HVAC systems, evaluate targeted light
levels [21], assess the environmental impacts of change orders, and evaluate and compare performance
of different materials or equipment options when selecting manufacturers, subcontractors, and material
suppliers [6,8].
BEM is also useful to contractors for material documentation during the construction phase [1]. For
example, material documentation is necessary to obtain LEED credit points related to reusable/recyclable
material selection (Materials and Resources Credits), and non-toxic materials (Indoor Environmental
Quality Credits) [1,29]. Azhar et al. [1] demonstrated the usefulness of BEM by integrating BEM into a
Revit™-based BIM workflow for the purpose of material documentation. Azhar et al. [1] exported the
BIM model from Revit™ as a gbXML file and imported it into the BEM software IES VE™. The
software used the material takeoffs created in Revit™ to generate reports analyzing the building model
for compliance with LEED.
In their assessment of three BEM tools, Stadel et al. [26] noted certain limitations in the Green
Building Studio™ Revit Plugin and the IES VE™ Revit Plugin which included the inability to account
for energy consumption and greenhouse gas emissions related to material activities during the
construction phase (e.g., material transportation and processing).
2.4. Use of BEM in the Building Operation and Maintenance Phase
In the operation phase, BEM can be used to monitor actual building performance and identify building
systems that may not function properly [6,8,23]. If renovation or remodeling needs to be performed
during the maintenance phase, BEM can be used to identify the most energy efficient retrofit model [8].
In other words, for the purpose of improving building performance in the facility management phase,
BEM may be used to help identify errors in HVAC system operation, and predict potential energy
savings related to adjustments in system levels and building retrofits [30].
There are a few limitations on BEM use in the operations phase of the building lifecycle. For example,
evaluation of energy advanced buildings (e.g., zero-net-energy building) shows that the actual
performance of some of them is not as expected or designed [12]. Another limitation is BEM’s inability
to simulate building performance under realistic conditions. Simulating building energy performance
under realistic conditions, i.e., including occupant behavior, is needed in order to obtain more accurate
results [14,19,20,22]. Inaccurate input related to occupant behavior and building operation is a common
and substantial source of error in building performance simulations under realistic conditions [12,14].
Thus, understanding the difference between the actual and optimum behavior is very important [12].
Occupant behavior is typically represented by setting indoor temperature, and schedule of appliances,
lighting and HVAC systems [12,14]. These parameters are highly variable and unpredictable [14].
Meanwhile, these parameters also significantly affect actual energy consumption and building
performance [31].
Buildings 2015, 5 1367
A number of energy analysis studies have offered solutions to mitigate the disparities between
predicted occupancy and operation, and actual building occupancy and operation, and the resulting
energy model inaccuracies. One solution is to calibrate the energy model with measured data from actual
building operation [8,14]. Adjustments made to occupancy schedules and operational profiles can be
made based on the observations of actual building users to more accurately input when and to what
extent the building is occupied, and how certain building systems (e.g., operable windows, artificial
lighting, blinds, etc.) are operated [14]. This strategy is illustrated in a case study conducted by
Knight et al. [32], in which a survey of building occupants for an educational building in the U.K. was
used to generate detailed schedules and operational profiles for more than 300 spaces in the building
energy model. According to this study, the use of building occupant surveys and other post-occupancy
evaluations is considered a useful method to improve the energy model accuracy during building operation.
Jazizadeh et al. [20] noted that field studies that include occupant surveys was one of the methods
that can be used to assess occupants comfort. However, they thought that these field studies did not
reflect real-time occupant comfort on ongoing basis as surveys were typically conducted only once or
periodically. Therefore, Jazizadeh et al. [20] proposed a framework for human-building interaction for
thermal comfort which allows occupants to have personalized control of their thermal comfort as well
as of HVAC systems in office buildings. The framework applied a participatory sensing approach via
smart-phone application.
BEM can also be utilized during the building operation phase to synchronize energy model inputs
with a real-time data feed from actual building operation. This synchronization is used to both calibrate
the model with actual building performance and to optimize system operation. Platt et al. [33]
demonstrated how a live feed of measured data from actual building operation is used to continuously
update and calibrate the operational inputs in the energy model. Platt et al. [33] used a genetic algorithm
to define the energy model inputs to optimize model accuracy. They demonstrated how an energy model
can continuously be calibrated and adapted to the dynamism of various parameters that affect the actual
HVAC zone environment. Adaptive energy models can both increase model accuracy and improve
energy efficiency through the analysis of resultant parameter inputs and potential operational changes in
the actual building. The resultant inputs provided by the genetic algorithms and the data obtained by
post-occupancy evaluations provide insight into improving accuracy for energy models used in earlier
building lifecycle phases.
2.5. Evaluation of BEM Tools
The literature review in the previous subsections of this paper illustrated how BEM can be utilized
for a variety of purposes and in different phases of the building lifecycle. BEM tools are also tailored
to specific user groups (e.g., architects, engineers, contractors, and facility managers). Previous research
focused on evaluating existing BEM tools using a variety of criteria to assess BEM capabilities
and features.
Attia et al. [34] conducted a survey of architects involved in design of sustainable buildings in order
to evaluate existing BEM tools. Architects were asked to compare 10 major BEM tools using two
criteria: (1) usability and information management interface; and (2) integration of intelligent design
knowledge-base. In regard to usability and information management interface, architects expressed the
Buildings 2015, 5 1368
need for greater user-friendliness of the graphical user interface. Architects also expressed the need for
a 3D environment for the energy model, and the desire for generating comparative reports for different
design alternatives. In regard to the integration of the intelligent design knowledge-base, the survey
results showed that the most desired BEM capabilities were feedback on building code and rating system
compliances, ability to provide weather data, and extensive building component and system libraries.
Attia et al. [34] concluded that the 10 BEM tools examined did not meet the needs expressed by the
architects that responded to the survey, and that IES VE, eQuest, and HEED were the most “architect
friendly” BEM tools.
Azhar et al. [25] conducted an evaluation study in which they compared the capabilities, advantages,
and disadvantages of three BEM tools (Ecotect, Green Building Studio, and IES VE). They concluded
that IES VE was the strongest of the three BEM tools based on its range of analysis options.
Crawley et al. [11] compared 20 BEM tools in terms of their capabilities and features. The BEM
features included in the comparison were organized into the following categories: modeling features;
zone loads; building envelope; daylighting and solar; infiltration, ventilation and multi-zone airflow;
renewable energy systems; electrical systems; HVAC systems; HVAC equipment; environmental emissions;
economic evaluation; climate data availability; results reporting; validation; user interface, links to other
programs, and availability. This evaluation of BEM tools provided users with a checklist of capabilities
for the 20 BEM tools evaluated, and can be helpful for users with a specific set of BEM requirements.
3. Research Method
In order to accomplish the objectives of this research four primary tasks were executed: (1) Performing
an initial evaluation of the existing BEM tools; (2) Conducting a case study utilizing the top three BEM
tools identified in the initial evaluation; (3) Re-evaluating the top three BEM tools, and (4) Developing
a set of guidelines to aid BEM users in the evaluation, selection and use of the most appropriate BEM
tool in a specific lifecycle phase.
3.1. Initial Evaluation of Existing BEM Tools
A literature review was conducted to select the BEM tools for the initial evaluation. The 12 major
existing BEM tools selected for the initial evaluation were: Graphisoft EcoDesigner, Bentley Tas
Simulator V8i, Bentley Hevacomp Simulator V8i, Autodesk Ecotect, Autodesk Green Building Studio,
IES VE, DesignBuilder, Visual DOE 4.0, Energy10, EnergyPlus, eQuest and HEED. The four criteria
used in the initial evaluation were: interoperability, usability, available inputs, and available outputs.
Each criterion was assessed through a number of sub-criteria (Figure 1). The evaluation criteria and
sub-criteria were identified based on the literature review. The scoring system in this study placed an
even weight of maximum 1 point for each criterion satisfied with a criterion score based on the
percentage of the sub-criteria supported by the BEM tool. For example, the interoperability criterion
included five sub-criteria: interoperability with Revit, Archicad, SketchUp, DXF import and gbXML
import. If a BEM software tool scored 1 for each interoperability sub-criterion, the total score at the
sub-criteria level would be 5. Based on this maximum total score for all sub-criteria, the achieved score
for the interoperability criterion would be equal to 1.
Buildings 2015, 5 1369
Figure 1. Initial evaluation scoring system with criteria and sub-criteria.
3.2. Case Study
A case study was conducted to illustrate the application of BEM tools. The top three BEM tools
identified in the initial evaluation stage were used in the case study. The performances of two buildings
located on a University campus in Gainesville, Florida, USA: Rinker Hall (a LEED gold-certified
building) and Gerson Hall (a non-LEED certified building) were compared. BIM models of each
building were created using the Revit Architecture software. Each model was exported as a gbXML file
from Revit Architecture to each of the three BEM tools. Specifications pertinent to each building’s
performance were input into the BEM tools (Table 1). Each BEM tool was used to simulate the
buildings’ performance in three categories: annual energy usage, daylighting, and natural ventilation.
Comprehensivescore
Ʃc
 WithRevit
 WithArchicad
 WithSketchUp
 DXFImport
 gbXMLimport
 Simpleuserinterface
 Providesextensiveweather/
climatefile
 Defaultlibraries
 Requiresminimalexpertise
 Helpfile
 Usertutorials/onlinesupport
 Potentialforcustomization
 Providesfeedbackforpotential
designchangestoimproveenergy
efficiency
 Floorplan
 Openings
 MaterialProperties
 Numberoffloors
 OpenGLmodel
 Location
 gbXMLmodel
 Buildi nggeometry
 Envelopeconstruction
 HVACtype
 HVACsizing
 MEPmodel
 Plantdata
 Occupancy
 Lightingsystem
 Interiorobjects
 Weatherdata
 Orientation
 Numberofroo ms
 Roomconnections
 Relationtoext.exposure
 Buildi ngtype/function
 Setting(localterrain )
 Requiredindoortemperature
 Typeofenergyused
 Energyusage
 Carbonemissions
 Resourcemanagement
 Thermalanalysis
 Heating/coolingload
 HVAC
 Natura lventilation
 Solaranalysis
 Daylighting
 Righttolight
 Shadingdesign
 Lightingdesign
 Lifecycleassess ment
 Lifecyclecost
 Waterusage
 PVcollectionpo tent ial
 Windenerg ypotential
 Wholebu ildi ngenergy
analysis
 LEEDintegrationtools
 EnergyStarintegration
tools
Interoperability
c1=x/5
Usability
c2=x/8
Availableinputs
c3=x/25
Availableoutputs
c4=x/20
Criteriaforevaluation
(x=numberofsubcriteria
supported byBEMtool)
Subcriteria
Buildings 2015, 5 1370
Table 1. Specifications of buildings used in the case study.
Building Characteristics LEED Certified Non-Certified
Date of completion 2003 2004
Location Gainesville, FL, USA Gainesville, FL, USA
Area of conditioned space 3969 sq·m 3589 sq·m
HVAC system Variable Air Volume with Energy
Recovery Ventilation Variable Air Volume with Terminal Reheat
Building envelope construction
(from exterior to interior)
1.9 cm metal panel, 14 cm R20
cellulose insulation, 5.1 cm rigid
insul., 1.3 cm gypsum board
10.2 cm brick veneer, 5.1 cm air gap/damproofing, 30.5 cm
CMU, 1.6 cm GWB on 3.8 cm studs with rigid insul.
Exterior wall U-Value 0.033 0.097
Glazing type Low-E, double-glazed, insulated Low-E, double-glazed
Glazing U-Value 0.53 0.66
Window-to-Wall Area Ratio 0.22 0.20
Albedo (Roof Reflectance) 0.80 0.41
3.3. Re-Evaluation of Top Three BEM Tools
Upon completion of the case study, a re-evaluation of the top three BEM tools was performed using
an updated set of criteria. Information gathered during the case study was used to revise the scoring
system used in the initial evaluation and develop a new set of criteria and sub-criteria to be used in the
re-evaluation phase (Figure 2). In addition to the criteria used in the initial evaluation, the scoring system
in the re-evaluation phase included the additional criteria of speed and accuracy. The speed of a BEM
tool was evaluated based on the amount of time needed to perform simulations of energy usage,
daylighting, and natural ventilation. Accuracy was assessed based on the percent differences between
the simulation results and actual/measured data for the two buildings. The re-evaluation scoring system
also added a few new sub-criteria to the two criteria (i.e., to available inputs and available outputs).
The best BEM tool was selected by evenly weighting each of the six criteria. A matrix that applies
different weights to criteria based on order of importance for the potential user was developed. Using
this approach, potential BEM users can use the matrix by first identifying the order of importance of the
six criteria, and then selecting the best BEM tool relative to the user’s criteria preference.
3.4. Development of Guidelines for Selecting, Evaluating and Using BEM Tools
Guidelines for BEM evaluation, selection and application were developed using data gathered in the
re-evaluation phase of this research and organized around the various building lifecycle phases (such as
design, construction and facility management) in which BEM can be applied.
Buildings 2015, 5 1371
Figure 2. Re-evaluation scoring system with criteria and sub-criteria.
4. Results
4.1. Results of Initial Evaluation of the Existing BEM tools
The top three BEM tools identified by the initial evaluation had a score larger than 3 points. IES VE™
scored 3.38 (out of 4 possible points), Ecotect™ scored 3.14, and Green Building Studio™ had a score
of 3.06 (Figure 3). The major factors that distinguished these three tools from the other tools were high
interoperability and available outputs. eQuest which had the fourth highest score did not perform well
in regards to interoperability and usability as compared to the top three BEM tools. For more details on
initial evaluation and calculations of the scores, see Appendix, Tables A1–A6.
4.2. Results of the Case Study
The top three BEM tools identified by the initial evaluation (IES VE, Ecotect, and Green Building
Studio) were used in the case study. Simulations of each building were performed using each BEM tool
to assess energy usage, daylighting, and natural ventilation in order to understand the process of using
the BEM tools. The secondary objective of conducting the case study was to compare the environmental
performance of the two buildings.
Comprehensivescore
Ʃc
 Geometrytransl ation(fr om
Revit)
 Materialtransl ation(from
Revit)
 Openingstransl ation(from
Revit)
 SketchUpplugin
 ImportCADgeometry(DXF)
 ImportIFC
 ImportgbXML
 ExportanalysisdatatoExcel
 Helpfile
 Userforum
 Simpleuserinterface
 Defaultlibraries/templates
 gbXMLimporterrorcheck
 Errorcheck duringsimulation
 Automaticreportgenerator
 Graphicaluserinterface(GUI)
 Requiresminimalexpertise
 Designalternativ eassista nce
 AbilitytoeditmodelinBEM
Availableinputs
 HVACtype
 Heatrecoverysystem
 Glazingspecifications
 Automatedlightingcont rols
 Construction(wall,roof,floor)
 Albedo
 Shadewall/louvers
 Lightingpowerdensity(LPD)
 HVACdesignflow
 Localterrain
 Geographiclocation/climate
 Occupancyschedule
 Equipment/lightingsche dule
 HVACschedule
 Heating/coolingsetpoi nts
 Equipmentpowerdensity
 Fueltype
 Systemenergyefficiency
 Userdefinedfanpower
 Operablewindows
 Operablewindowsschedule
Availableoutputs
 Energyusage
 Carbonemissions
 Resourcemanagement
 Thermalanalysis
 Heating/coolingload
breakdown
 Solaranalysis
 Daylightingassessm ent
 Lightingdesign
 Lifecyclecostanal ysis
 Ventilationan dairflow
analy sis
 Waterusage
 Designalternativ e
comparison
Interoperability
c1=x/8
Usability
c2=x/11
Availableinputs
c3=x/29
Availableoutputs
c4=x/18
Criteriaforevaluation
(x=numberofsubcriteria
supported byBEMtoolor
sumofpercentaccuracy
foraccur acycriterion)
Subcriteria
Speed
c5=x/6
Accura cy
C6=x/2
Versatilityofinputs
 Userdefinedconstructions
 Userdefinedoccupancysch edule
 Userdefinedequipment/lightingschedules
 Userdefinedheating/coolingschedules
 Userdefinedsystems(HVAC)
 Userdefinedtimestepforcalculations
 Zonebyzon einputs
 Modelbuild er
Versatilityofoutputs
 Userdefinedtimestep
 Userdefinedreports/
graphicaloutputs
 Graphicalanalysisover
model
 Animation
 Room/zonelevelanalysis
 Graphicalcomparison
betweendesigniterations
 Energysimulationunder1hr
 Energysimulationunder10
min
 Daylightingsimulationunder
1hr
 Daylightingsimulationunder
10min
 Ventilationsimulationunder
1hr
 Ventilationsimulationunder
10min
 Perce ntofaccuracyof
theLEEDcertified
building
 Perce ntofaccuracyof
noncertifiedbuilding
Buildings 2015, 5 1372
Figure 3. Initial evaluation scores.
The simulation results of energy usage showed that Rinker Hall, the LEED gold-certified building,
performed better than Gerson Hall, the non-certified building. Energy use intensity (EUI) was used as
the metric to compare energy performance, because EUI eliminates any differences between the two
buildings’ energy consumption that may be attributed to differences in areas of conditioned space. The
LEED certified building performed better than non-certified building in terms of total annual energy
usage as well as energy use intensity (Figure 4). This finding was consistent for the simulation results
obtained by using all three BEM tools.
The Ecotect simulation results showed that the LEED certified building would consume less energy
than non-certified building (56% difference between EUIs). Simulation results obtained from Green
Building Studio also showed that the LEED certified building would consume less energy than the
non-certified building (20% difference between EUIs). Similarly, the IES VE simulations estimated that
the LEED certified building would consume less energy than the non-LEED certified building (36%
difference between EUIs). Both the Ecotect and the Green Building Studio simulation results showed
that both buildings have EUI lower than the median value of 328 kWh/sq·m recommended by U.S.
Energy Information Administration [35]. In the case of the IES VE simulation results, the
non-certified building has an EUI higher than the median value of 328 kWh/sq·m, while the EUI of the
LEED certified building was lower than 328 kWh/sq·m.
Four rooms from each building were selected to compare the daylighting performance (Table 2).
Similar rooms based on room function, area, and glazing orientation in the two buildings were compared
using daylight factor as the common parameter that was available as the output of the three BEM tools.
Buildings 2015, 5 1373
Figure 4. Energy use intensity (EUI) comparison by building and by building energy
modeling (BEM) tool. Dashed line denotes the national median EUI for educational building
types (328 kWh/sq·m).
Table 2. Characteristics of the rooms used in daylighting analysis.
LEED Certified Building Non-Certified Building
Room Function Area (sq·m) Glazing Orientation Room Function Area (sq·m) Glazing Orientation
Main Conference 55 North Large Conference 71 North
Faculty Office 13 West Office 14 North
Est./Dwg./Sch. Class. 124 East Medium Classroom 108 East
Grad. Stud. Office 49 East PhD Office 25 North
Daylighting performances of the two buildings could be compared within each BEM tool, but results
could not be compared between the three BEM tools due to the fact that the daylight factor was not
calculated in a consistent manner. Only Ecotect and IES VE allow the user to specify in the model the
location of the sensor points at which the daylight level is measured. None of the three BEM tools allows
the user to specify the date and time at which the daylight factor is calculated.
The rooms in the LEED certified building, with some exceptions, had higher daylight factors than
their counterparts in the non-certified building (Table 3). According to the simulation results obtained
from each BEM tool, the LEED certified building’s conference room, classroom, and graduate student
office suite performed better than those in the non-certified building. The faculty office had mixed results
based on the Ecotect and Green Building Studio simulation results that predicted higher daylight factors
in the faculty office in the non-certified building. However, IES VE simulation results showed that the
faculty office in the LEED certified building performed better.
Buildings 2015, 5 1374
Table 3. Comparison of daylight factors (for the selected rooms and the three building
energy modeling (BEM) software). Bolded values are greater than the minimum required
daylight factor (2%) for adequate daylighting.
Room Function Building IES VE Ecotect Green Building Studio
Conference Room LEED certif. 13.70% 11.48% 6.30%
non-certified 4.80% 3.37% 0.70%
Faculty Office LEED certif. 6.40% 2.74% 0.30%
non-certified 5.00% 3.22% 1.00%
Classroom LEED certif. 3.80% 3.98% 0.80%
non-certified 1.10% 3.00% 0.20%
Grad. Stud. Office LEED certif. 2.60% 3.89% 0.90%
non-certified 3.10% 1.79% 0.50%
Each of the three BEM tools uses a different method to evaluate natural ventilation. Potential energy
savings from natural ventilation were calculated in the Ecotect by subtracting the overall energy use of
the models with natural ventilation activated from energy use values of the benchmark models. The
Ecotect simulations showed that the non-certified building (potential savings of 142,043 kWh) could
possibly save more energy (35% difference) than the LEED certified building (potential savings of
92,516 kWh). Green Building Studio provided outputs related to the amount of energy that could be
saved through the use of natural ventilation. The Green Building Studio simulations showed that the
non-certified building (potential savings of 57,883 kWh) could possibly save more energy (44%
difference) through natural ventilation than the LEED certified building (potential savings of
32,254 kWh). IES VE assesses natural ventilation by providing average annual infiltration rates in units
of cubic decimeters per minute (cu dm m) per square meter for each zone. The non-certified building
had an average natural ventilation rate of 10.1 cu dm m per square meter averaged over the entire
inhabitable building floor area compared to LEED certified building’s average natural ventilation rate
of 6.7 cu dm m per square meter. Thus, the non-certified building seemed to have a 33% higher
ventilation rate than the LEED certified building.
4.3. Results of Re-Evaluation of the Top Three BEM Tools
Based on the re-evaluation, IES VE had the highest comprehensive score (4.34 out of 6 possible
points) when criteria were weighted equally (Figure 5). Green Building Studio achieved the score of
3.44, while Ecotect scored 3.40 points. Out of the six different criteria used in the re-evaluation, IES VE
received the highest criterion score for four criteria. IES VE had the same score as the Ecotect in the
criterion for interoperability, and the second highest score in the criterion of speed after the Green
Building Studio. Ecotect and IES VE achieved the highest scores (score 0.61) in the criterion of
interoperability followed by the Green Building Studio (score 0.33). IES VE had the highest score in the
criterion of usability (score 0.73), while Green Building Studio followed with a score of 0.59 and Ecotect
with a score of 0.55. IES VE also had the highest score in the criterion of available inputs with a score
of 0.95, followed by Ecotect (score 0.91) and Green Building Studio (score 0.45). Regarding the criterion
available outputs, IES VE had the highest score of 0.86, followed by Ecotect (score 0.81) and Green
Building Studio (score 0.56). Green Building Studio had the highest score in the criterion of speed (1.00)
Buildings 2015, 5 1375
followed by IES VE 1 (score 0.5) and Ecotect (score 0.0). Regarding the criterion of accuracy, IES VE
achieved the highest score based on percent difference between the simulation results and the measured
data for the two buildings used in the case study. IES VE’s accuracy score was 0.69 followed by Ecotect
and Green Building Studio, each of which obtained a score of 0.52. For more details on re-evaluation
and calculations of the scores, see Appendix, Tables A7–A12.
Figure 5. Re-evaluation scores (un-weighted).
4.4. Guidelines for Evaluation, Selection and Application of BEM Tools
Existing BEM tools are diverse in terms of capabilities, inputs, outputs, and applicability in various
building lifecycle phases. The guidelines developed by this research are meant to assist potential BEM
users in evaluating and selecting the appropriate BEM tool for the user’s intended BEM application. The
guidelines for BEM evaluation and selection include the following steps (Figure 6):
Step 1—Defining the building lifecycle phases in which the BEM tool is intended to be utilized.
Step 2—Defining the required inputs as necessary to utilize the BEM for the specified building
lifecycle phase applications, and then using these inputs as a checklist of prerequisites when
evaluating and selecting BEM tool.
Step 3—Defining the required outputs and using them as a checklist of prerequisites when
evaluating and selecting BEM tool.
Step 4—Ranking other criteria for BEM evaluation and selection (e.g., interoperability, usability,
and speed) in order of importance.
Step 5—Applying appropriate weights to the criteria (based on order of importance) and
calculating the scores of the BEM tools that meet the prerequisites defined by steps 1 through 3.
Buildings 2015, 5 1376
Figure 6. Guidelines for BEM tool evaluation and selection.
The steps of the BEM evaluation and selection process are related to the corresponding tables for
required inputs, user-defined required outputs, and examples of other “soft” criteria for evaluation (e.g.,
interoperability and usability). Potential BEM users can use these guidelines as a template to develop
their own specific system for BEM tool evaluation and selection that would incorporate the criteria and
Buildings 2015, 5 1377
sub-criteria, which they find important for their project. Potential BEM users should first define the
building lifecycle phases in which the BEM tool will be utilized. Certain BEM tools are geared only
towards early design stages while others carry a wide range of capabilities and may be useful from the
conceptual design to the facility management phase. The range of available inputs from a BEM tool is
indicative of its applicability in various building lifecycle phases. Secondly, BEM users should ensure
that the necessary inputs are included for the building lifecycle phases in which they intend to use BEM.
For instance, BEM users that plan to use BEM in later building lifecycle phases, such as the facility
management phase, should ensure that the BEM tool allows inputs for occupancy schedule, lighting
schedule, equipment schedule, and plant data in order to calibrate the model with actual building
operation. The degree of versatility of schedule implementation is particularly important. The capability
of inputting user-defined schedules is necessary for calibrating the energy model with actual data
obtained from building operation. These inputs should be treated as prerequisites to later BEM evaluation
and selection criteria. Thirdly, BEM users should define a set of required outputs. These may serve as a
checklist for users of the guidelines and may be considered prerequisites to later BEM evaluation and
selection criteria. This step of the guidelines asks users to define the simulation and analysis types the
user intends to perform with the BEM tool. The available outputs checklist is intended to be used to shortlist
BEM tools that meet the user’s required outputs.
After narrowing down the potential BEM tools based on the user’s required inputs and outputs, other
criteria may be integrated into the evaluation and selection process. These potential criteria for evaluation
and selection can then be ranked in the user’s order of importance. Other criteria, such as those used in this
research, may include usability, interoperability, and speed of simulation. Based on the user’s order of
importance for these criteria, appropriate weightings can be applied for scoring purposes. For example,
the most important criterion may multiply the respective score in the initial evaluation by three; the
second most important criterion may multiply the score by two; and the third most important criterion
may multiply the respective score by one. The weighted scores can then be added together to provide a
cumulative score that should indicate the most appropriate BEM tool for the user’s specified BEM
applications in a specific building lifecycle phase.
5. Conclusions
The various existing building energy modeling (BEM) tools present a wide range of capabilities and
applications. Based on the criteria used to evaluate BEM tools in this research, IES VE was selected as
the most appropriate BEM software when criteria were weighted evenly. However, the selection of
a BEM tool is dependent on how the user intends to apply BEM and how BEM is incorporated into
a design, construction and facility management workflow. For example, Green Building Studio may be
a more appropriate selection for users requiring a faster output to compare numerous design iterations
related to building specifications. As observed in the case study conducted in this research, there are also
numerous BEM methodologies that can be adopted for various applications. As suggested by previous
research, BEM has a wide range of applications spanning throughout the building lifecycle from
conceptual design through the building operation and maintenance phases. Thus, the guidelines are
intended to be used as a template that can be tailored to the specific needs of the user and intended
applications of BEM. This research aimed at developing methods that can be used to evaluate and select
Buildings 2015, 5 1378
BEM tools. The potential users of the evaluation methods can use them to evaluate different sets of
actual commercial BEM software tools as compared to the set of software used in this research. In that
case, they can still use the methods developed in this research for evaluating and selecting the most
appropriate BEM tool for their needs.
This research evaluated BEM tools in a broader scope given the wide range of BEM applications as
compared to previous BEM tool evaluations. The research contribution includes the development of
guidelines for the evaluation and selection of the BEM tools in regard to their application and usability
in different lifecycle phases of the building. As noted previously in this paper, previous research showed
the need for development of BEM guidelines because there are various BEM tools available and typical
project stakeholders (such as architects, contractors, and facility managers) find it often challenging to
evaluate, select and use some of the BEM tools.
Author Contributions
This research is based on Thomas Reeves’ Master’s research. He conducted the research under the
supervision of Svetlana Olbina who designed this research. Raja R. A. Issa was a co-chair of Thomas’
Master’s committee. All three authors contributed equally to writing of the paper.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix
Table A1. Initial evaluation: interoperability criterion calculations for BEM tools.
BEM Tool With Revit With Archicad With
Sketch Up DXF Import gbXML Import Total Points
(Out of 5) Percentage Score
HEED 0 0 0 0 0 0 0.0
IES VE 1 1 1 1 1 5 1.0
Energy-10 0 0 0 0 0 0 0.0
EnergyPlus 0 0 1 0 0 1 0.2
Visual DOE 4.0 0 0 0 1 0 1 0.2
Design Builder 0 0 0 1 0 1 0.2
Hevacomp Simulator V8i 1 1 0 1 1 4 0.8
Ecotect 1 1 0 1 1 4 0.8
Green Building Studio 1 1 0 1 1 4 0.8
Tas V8i 1 1 0 1 1 4 0.8
EcoDesigner 1 1 0 1 1 4 0.8
eQuest 1 0 0 1 1 3 0.6
Buildings 2015, 5 1379
Table A2. Initial evaluation: usability criterion calculations for BEM tools.
BEM Tool
Simple
User
Interface
Provides Extensive
Weather/Climate
Data
Default
Libraries
Requires
Minimal
Expertise
Help
File
User
Tutorials/Online
Support
Potential for
Customization
Provides Feedback
for Potential Design
Changes to Improve
Energy Efficiency
Total
Points
(Out
of 8)
Percentage
Score
HEED 1 0 1 1 1 1 0 1 6 0.75
IES VE 1 1 1 0 1 1 0 0 5 0.63
Energy-10 1 1 1 0 1 1 0 1 6 0.75
EnergyPlus 0 1 1 0 1 1 0 0 4 0.50
Visual DOE 4.0 0 1 1 0 1 1 1 0 5 0.63
Design Builder 1 0 1 1 1 1 0 0 5 0.63
Hevacomp Simulator V8i 0 1 1 0 1 1 0 0 4 0.50
Ecotect 0 1 1 0 1 1 1 0 5 0.63
Green Building Studio 1 1 1 0 1 1 0 1 6 0.75
Tas V8i 0 1 1 0 1 1 0 0 4 0.50
EcoDesigner 0 1 1 0 1 1 0 0 4 0.50
eQuest 0 1 1 0 1 1 0 0 4 0.50
Table A3. Initial evaluation: available inputs criterion calculations for BEM tools (Part 1).
BEM Tool HEED IES VE Energy-10 EnergyPlus Visual DOE 4.0 Design Builder
Floor plan 1 1 0 0 1 1
Openings 1 1 1 1 1 1
Material properties 0 1 1 1 1 1
Number of floors 1 0 1 1 0 0
OpenGL model 0 0 0 0 0 1
Location 1 1 1 1 1 0
gbXML model 0 1 0 0 0 0
Building geometry 0 1 0 0 1 1
Envelope construction 1 1 1 1 1 1
Buildings 2015, 5 1380
Table A3. Cont.
BEM Tool HEED IES VE Energy-10 EnergyPlus Visual DOE 4.0 Design Builder
HVAC system 0 1 1 1 1 1
HVAC sizing 0 1 0 1 0 0
MEP model 0 1 0 0 0 0
Plant data 0 1 0 1 0 0
Occupancy 0 1 0 1 1 1
Lighting system 0 1 0 1 1 1
Interior objects 0 0 0 0 0 0
Weather data 1 1 1 1 1 0
Orientation 0 1 1 1 1 0
Number of Rooms 0 1 0 1 0 0
Room connections 0 1 0 1 0 0
Relation to exterior exposure 0 0 0 0 0 0
Building type/function 0 1 0 0 1 1
Setting (local terrain) 0 0 0 0 0 0
Required indoor temperature 0 1 0 1 0 0
Type of energy used 0 1 0 0 0 0
Total points (Out of 25) 6 20 8 15 12 10
Percentage Score 0.24 0.8 0.32 0.6 0.48 0.4
Buildings 2015, 5 1381
Table A4. Initial evaluation: available inputs criterion calculations for BEM tools (Part 2).
BEM Tool Hevacomp Simulator V8i Ecotect Green Building Studio Tas V8i EcoDesigner eQuest
Floor plan 1 1 1 1 1 1
Openings 0 1 1 0 1 1
Material properties 0 1 1 1 0 1
Number of floors 0 0 0 0 0 1
OpenGL model 0 0 0 0 0 0
Location 1 1 1 1 1 1
gbXML Model 1 1 1 1 1 1
Building geometry 1 1 1 1 1 1
Envelope construction 1 1 1 1 0 1
HVAC system 1 1 1 0 1 1
HVAC sizing 1 1 0 0 1 0
MEP model 0 0 0 0 0 0
Plant data 0 0 0 1 1 1
Occupancy 0 1 0 1 0 1
Lighting system 0 1 0 0 0 1
Interior objects 1 0 0 0 0 0
Weather data 1 1 1 1 1 1
Orientation 0 1 1 0 1 1
Number of Rooms 0 1 1 0 0 1
Room connections 0 1 1 0 0 0
Relation to exterior exposure 0 0 1 0 0 0
Building type/function 0 1 1 0 1 1
Setting (local terrain) 0 1 0 0 0 0
Required indoor temperature 0 1 0 0 1 1
Type of energy used 0 1 0 0 1 1
Total points (Out of 25) 9 19 14 9 13 18
Percentage Score 0.36 0.76 0.56 0.36 0.52 0.72
Buildings 2015, 5 1382
Table A5. Initial evaluation: available outputs criterion calculations for BEM tools (Part 1).
BEM Tool HEED IES VE Energy-10 EnergyPlus Visual DOE 4.0 Design Builder
Energy usage 1 1 1 1 0 1
Carbon emissions 1 1 1 1 0 1
Resource management 0 1 0 0 0 0
Thermal analysis 1 1 1 1 1 1
Heating/cooling load 0 1 1 1 1 1
HVAC 1 1 0 1 1 1
Natural ventilation 1 1 1 1 0 1
Solar analysis 0 1 1 1 0 1
Daylighting 1 1 1 1 1 1
Right-to-light 0 1 0 0 0 0
Shading design 0 1 0 0 0 1
Lighting design 0 1 0 1 1 1
Lifecycle assessment 0 1 0 0 0 0
Lifecycle cost 1 1 1 0 0 0
Water usage 0 1 0 1 0 0
PV collection potential 1 1 1 0 0 0
Wind energy potential 0 1 0 0 0 0
Whole building energy analysis 0 1 1 1 0 0
LEED integration tools 0 1 1 0 1 0
Energy Star integration tools 0 0 0 0 0 0
Total points (Out of 20) 8 19 11 11 6 10
Percentage Score 0.4 0.95 0.55 0.55 0.3 0.5
Buildings 2015, 5 1383
Table A6. Initial evaluation: available outputs criterion calculations for BEM tools (Part 2).
BEM Tool Hevacomp Simulator V8i Ecotect Green Building Studio Tas V8i EcoDesigner eQuest
Energy usage 1 1 1 1 1 1
Carbon emissions 0 1 1 1 1 1
Resource management 0 1 1 0 0 0
Thermal analysis 1 1 1 1 1 1
Heating/cooling load 1 1 1 1 1 1
HVAC 1 1 1 1 1 1
Natural ventilation 1 1 1 1 0 1
Solar analysis 1 1 1 0 0 1
Daylighting 1 1 1 1 1 1
Right-to-light 0 1 0 0 0 0
Shading design 1 1 1 1 0 1
Lighting design 0 1 1 0 0 0
Lifecycle assessment 0 0 1 0 0 1
Lifecycle cost 0 1 1 1 0 1
Water usage 0 1 1 0 0 1
PV collection potential 1 1 1 0 0 1
Wind energy potential 1 1 1 0 0 0
Whole building energy analysis 1 1 1 0 0 1
LEED integration tools 0 1 1 1 0 0
Energy Star integration tools 0 1 1 0 0 0
Total points (Out of 20) 11 19 19 10 6 14
Percentage Score 0.55 0.95 0.95 0.5 0.3 0.7
Buildings 2015, 5 1384
Table A7. Re-evaluation: interoperability criterion calculations for the top three BEM tools.
Interoperability Sub-Criteria Ecotect Green Building Studio IES VE
Geometry translation (from Revit) 0.5 0.5 0.5
Material translation (from Revit) 0.5 0 0.5
Openings translation (from Revit) 0.5 0.5 0.5
SketchUp plugin 0 0 1
Import CAD geometry (DXF) 1 0 1
Import IFC 1 0 0
Import gbXML 1 1 1
Export analysis data to Excel 1 1 1
Total points (out of 8) 5.5 3 5.5
Percentage score 0.61 0.33 0.61
Table A8. Re-evaluation: usability criterion calculations for the top three BEM tools.
Usability Sub-Criteria Ecotect Green Building Studio IES VE
Help file 1 1 1
User forum 1 1 1
Simple user interface 0 1 0
Default libraries/templates 1 1 1
gbXML import model error check 0 0 1
Error check during simulation 1 0 1
Automatic report generator 0 1 1
Graphical User Interface (GUI) 1 0 1
Requires minimal expertise 0 0.5 0
Design alternative assistance 0 1 0
Ability to edit model in BEM 1 0 1
Total points (out of 11) 6 6.5 8
Percentage score 0.55 0.59 0.73
Table A9. Re-evaluation: available inputs criterion calculations for the top three BEM tools.
Available Inputs Sub-Criteria Ecotect Green Building Studio IES VE
Available inputs
HVAC type 1 1 1
Heat recovery system 1 0 0
Glazing specifications (low-e, tint, U value, visible transmittance) 1 1 1
Automated lighting controls 1 1 1
Construction (walls, roof, floor) 1 1 1
Albedo 1 1 1
Shade walls/louvers 1 0 1
Lighting power density (LPD) 1 1 1
HVAC design flow 1 0 1
Local terrain 1 1 1
Geographic location/climate 1 1 1
Occupancy schedule 1 0 1
Equipment/lighting schedule 1 0 1
Buildings 2015, 5 1385
Table A9. Cont.
Available Inputs Sub-Criteria Ecotect Green Building Studio IES VE
HVAC schedule 1 0 1
Heating/cooling setpoint 1 1 1
Equipment power density 1 1 1
Fuel type 1 1 1
System energy efficiency 1 0 1
User-defined fan power 1 0 1
Operable windows 0 1 1
Operable windows schedule 0 0 1
Versatility of inputs
User-defined constructions 1 0.5 1
User-defined occupancy schedule 1 0 1
User-defined equipment/lighting schedule 1 0 1
User-defined heating/cooling schedule 1 0 1
User-defined systems (HVAC) 1 0.5 1
User-defined time step for calculations 0.5 0 0.5
Zone-by-zone inputs 1 0 1
Model builder 1 0 1
Total points (out of 29) 26.5 13 27.5
Percentage score 0.91 0.45 0.95
Table A10. Re-evaluation: available outputs criterion calculations for the top three BEM tools.
Available Outputs Sub-Criteria Ecotect Green Building Studio IES VE
Available outputs
Energy usage 1 1 1
Carbon emissions 1 1 1
Resource management 1 1 1
Thermal analysis 1 0 1
Heating/cooling load breakdown 1 1 1
Solar analysis 1 0 1
Daylighting assessment 1 1 1
Lighting design 1 0 1
Lifecycle cost analysis 1 1 1
Ventilation and airflow analysis 1 1 1
Water usage 1 1 0
Design alternative comparison 0 1 0
Versatility of
outputs
User-defined time step 0.5 0 0.5
User-defined reports/graphical outputs 1 0 1
Graphical analysis over model 1 0 1
Animation 0 0 1
Room/zone level analysis 1 0 1
Graphical comparison between design iterations 0 1 1
Total points (out of 18) 14.5 10 15.5
Percentage score 0.81 0.56 0.86
Buildings 2015, 5 1386
Table A11. Re-evaluation: speed criterion calculations for the top three BEM tools.
Speed Sub-Criteria Ecotect Green Building Studio IES VE
Energy simulation time under 1 h 0 1 1
Energy simulation time under 10 min 0 1 0
Daylighting simulation time under 1 h 0 1 1
Daylighting simulation time under 10 min 0 1 0
Ventilation simulation time under 1 h 0 1 1
Ventilation simulation time under 10 min 0 1 0
Total points (out of 6) 0 6 3
Percentage score 0 1 0.5
Table A12. Re-evaluation: accuracy criterion calculations for the top three BEM tools.
Accuracy Sub-Criteria Ecotect Green Building Studio IES VE
LEED certified building 32.37 52.09 51.90
Non-certified building 71.11 52.78 85.45
Total Points (out of 200) 103.48 104.87 137.35
Percentage score 0.52 0.52 0.69
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