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INOM EXAMENSARBETE SAMHÄLLSBYGGNAD,AVANCERAD NIVÅ, 30 HP
, STOCKHOLM SVERIGE 2017
Use of Building Energy Simulation Software in Early-Stage of Design Process
Användning av energisimuleringsprogram i tidiga skeden av byggprocessen
BEIDI LI
KTHSKOLAN FÖR ARKITEKTUR OCH SAMHÄLLSBYGGNAD
Use of Building Energy Simulation
Software in Early-Stage of Design
Process
Användning av energisimuleringsprogram i tidiga
skeden av byggprocessen
BEIDI LI
Degree Project No. 459, 2017
KTH Royal Institute of Technology
Division of Building Technology
Department of Civil Engineering and Architecture
SE-100 44 Stockholm, Sweden
Abstract
In traditional planning process, energy analysts work on finalized architectural designs and
have limited capability to amend inefficient energy features such as high aspect ratio.
Energy efficiency being a major part of sustainable design, the need for performance-
oriented design tools has become imminent.
There is a wide range of energy simulation tools across the world. Crawley et al. (2005) [1]
proposes a plain comparison of the most common ones based on vendor-supplied
information. The present report aims to identify simulation tools that can help architects
making energy-efficient design decisions in early stage of building process and the most
suitable programs will be tested on a standard case in Stockholm area with respect to their
architecture, functionalities, usability and limitations.
Keywords Building energy simulation, performance-based design, Delphi method, multi-criteria
decision analysis
Preface
The present master thesis has been conducted as the degree project of the MSc program
Civil and Architectural Engineering at KTH Royal Institute of Technology from July to
November 2017.
The project has been carried out after an initiative from Stockholms
Stadsbyggnadskontoret and Familjebostäder. The company’s supervisor for this project has
been Jasenka Hot, WSP Environmental. Folke Björk, professor at Department of Civil
Engineering and Architecture, KTH, has also been supervising the work.
I would like to thank these people along with the staff at WSP Environmental who have
been supportive during the work.
I would also like to express my appreciation to the companies Graphisoft AB who have
provided us with licenses for the ArchiCAD add-on EcoDesigner Star and Passiv Haus
Institute for the SketchUp plug-in designPH.
I was given the maximum freedom to explore my interests in the field and the project has
enhanced my will to contribute to a sustainable society. The scientific investigation being a
continuous process, hopefully the experience and knowledge I am about to present are
useful for future developments.
Stockholm, November 2017
Beidi Li
Contents
Introduction .................................................................................................................. 16
Background ............................................................................................................ 16
Aim ........................................................................................................................ 16
Method ................................................................................................................... 16
Limitations .............................................................................................................. 16
Scoping ........................................................................................................................ 17
BES theory ............................................................................................................. 17
Performance-based design tools ............................................................................ 18
Program validation ................................................................................................. 19
Screening ..................................................................................................................... 21
Identification of relevant energy features ................................................................ 21
Description of state-of-the-art BES software .......................................................... 22
Thermal simulation engines and derived user interfaces ................................. 23
In Nordic countries ........................................................................................... 27
CAD program-integrated tools ......................................................................... 33
Autodesk family ......................................................................................... 33
ArchiCAD .................................................................................................. 35
Third-party plug-ins ................................................................................... 36
Rhinoceros 3D .......................................................................................... 38
Other software ................................................................................................. 39
Assessment criteria ................................................................................................ 42
Selection ...................................................................................................................... 43
Test .............................................................................................................................. 44
Stockholmshus case .............................................................................................. 44
Revit ................................................................................................................ 44
Energy Analysis ........................................................................................ 45
Insight ....................................................................................................... 46
Green Building Studio (GBS) .................................................................... 46
ArchiCAD......................................................................................................... 47
Energy Evaluation (EE) ............................................................................. 48
EcoDesigner ............................................................................................. 49
SketchUp ......................................................................................................... 49
Sefaira Systems ........................................................................................ 49
OpenStudio ............................................................................................... 51
designPH .................................................................................................. 51
Design alternatives of three typical residential buildings ......................................... 52
ArchiCAD......................................................................................................... 53
SketchUp ......................................................................................................... 54
Sefaira ...................................................................................................... 54
designPH .................................................................................................. 55
Evaluation .................................................................................................................... 56
Delphi Method ........................................................................................................ 56
Decision matrix .......................................................................................................56
Results .........................................................................................................................57
Stockholmshus case ..............................................................................................57
Three typical building volumes ...............................................................................58
Multi-criteria decision analysis ................................................................................60
Limitations ....................................................................................................................61
Conclusion ....................................................................................................................63
Future perspectives ....................................................................................................64
Model calibration ..................................................................................................64
District level modelling ..........................................................................................64
Software reprogram ..............................................................................................65
References .................................................................................................................66
Workflow of Revit energy analysis applications ...........................................................70
Energy Analysis....................................................................................................71
Insight 360 ............................................................................................................72
Green Building Studio (.gbXML) ...........................................................................72
Workflow of ArchiCAD energy add-ons .......................................................................74
Energy Evaluation ................................................................................................74
EcoDesigner .........................................................................................................77
Workflow of SketchUp energy plug-ins........................................................................78
Sefaira Systems ...................................................................................................78
OpenStudio ..........................................................................................................80
designPH..............................................................................................................81
Annex A: Energy Analysis report for Stockholmshus ...................................................83
Annex B: Energy Evaluation report for Stockholmshus ...............................................84
Annex C: EcoDesigner report for Stockholmshus .......................................................85
Annex D: Comparative table of BES tools ...................................................................86
Figures
Fig 1 The MacLeamy Curve, source: [4] ..................................................................................... 17
Fig 2 Data exchange capabilities of eQUEST, source: [7] ....................................................... 18
Fig 3 Existing and desired BES tools, source: [3] ..................................................................... 19
Fig 4 Validation methodology in BESTEST, source: [20] ......................................................... 20
Fig 5 Predefined shape in eQUEST (3D view under Detailed Interface), source: [34] ....... 24
Fig 6 Simulation results in eQUEST, source: [34] ..................................................................... 24
Fig 7 3D isometric view in BDA .................................................................................................... 24
Fig 8 Result visualization in BDA ................................................................................................. 24
Fig 9 Editing window in DesignBuilder ........................................................................................ 25
Fig 10 Temperature and thermal simulation in DesignBuilder ................................................ 25
Fig 11 Extrusion and stacking of standard floor plan shapes, source: [38] ........................... 25
Fig 12 Outputs of whole building performance in Simergy, source: [38] ............................... 26
Fig 13 Wire-framed simulation geometry in DPV, source: [40] ............................................... 26
Fig 14 Energy balance breakdown in RevitPythonShell, source: [40] ................................... 26
Fig 15 Output window in ZEBO, source: [9] ............................................................................... 27
Fig 16 CAD interface in BSim, source: [42] ................................................................................ 27
Fig 17 Sunlight and shadow visualization in BSim, source: [42] ............................................. 27
Fig 18 CAD interface in BV2-arch ................................................................................................ 28
Fig 19 Energy balance calculations in BV2-arch ....................................................................... 28
Fig 20 General tab in IDA ICE at standard level, source: [44] ................................................ 28
Fig 21 Schematic tab in IDA ICE at advanced level, source: [44] .......................................... 29
Fig 22 Total heating and cooling simulation plots in IDA ICE, source: [44] .......................... 29
Fig 23 Building tab for primary systems in ESBO, source: [36] .............................................. 29
Fig 24 Room tab for secondary systems in ESBO, source: [36] ............................................. 29
Fig 25 Result tab in ESBO, source: [36] ..................................................................................... 30
Fig 26 Building-related parameters input window, source: [46] .............................................. 30
Fig 27 Energy balance in VIP, source: [46] ................................................................................ 30
Fig 28 EHK calculation sheet for single-family house, source: [49] ....................................... 31
Fig 29 Result summary, source: [49] ........................................................................................... 31
Fig 30 Creation of building elements in Derob, source: [50] .................................................... 31
Fig 31 Thermal comfort results in Derob, source: [50] ............................................................. 31
Fig 32 Simulink model in HAM-Tools, source: [52] ................................................................... 32
Fig 33 Annual energy consumption for heating and cooling, source: [51] ............................ 32
Fig 34 Window-related parameters in Energy-10, source: [53] ............................................... 32
Fig 35 Energy labels in Energy-10, source: [53] ....................................................................... 32
Fig 36 Sun path and shadow visualization in Ecotect, source: [54] ....................................... 33
Fig 37 Solar radiation in Vasari, source: [55] ............................................................................. 33
Fig 38 3D energy model in Revit for a single-family housing model ...................................... 34
Fig 39 FormIt web application interface ...................................................................................... 34
Fig 40 Heating loads visualization in Insight .............................................................................. 34
Fig 41 Simulation charts in GBS ................................................................................................... 35
Fig 42 A single-family dwelling model in ArchiCAD ................................................................... 35
Fig 43 Sefaira energy analysis view in Revit .............................................................................. 36
Fig 44 Sefaira energy and daylight analysis results in Revit .................................................... 36
Fig 45 VE SketchUp plug-in showing room construction types ............................................... 37
Fig 46 System loads in VE-Ware, source: [57] .......................................................................... 37
Fig 47 OpenStudio rendering by thermal zones in SketchUp .................................................. 38
Fig 48 Variable plot (site outdoor air wet bulb temperature) in ResultViewer ....................... 38
Fig 49 Workflows in designPH and PHPP, source: [60] ........................................................... 38
Fig 50 Grasshopper, Matlab, EnergyPlus and Radiance coupling, source: [62] .................. 39
Fig 51 Model viewing and result analysis in ESP-r, source: [63] ............................................ 39
Fig 52 Typical room properties in MIT Design Advisor ............................................................. 40
Fig 53 Monthly energy use for heating, cooling and lighting, source: [12] ............................. 40
Fig 54 3D Modeller in Tas, source: [64] ...................................................................................... 40
Fig 55 Results Viewer in Tas, source: [64] ................................................................................. 40
Fig 56 Web-based building portfolio, source: [65] ..................................................................... 41
Fig 57 Scenario analysis and energy optimization, source: [65] ............................................. 41
Fig 58 Result of parameter variation, source: [13] ..................................................................... 41
Fig 59 Two urban configurations, source: [18] ........................................................................... 65
Tables
Table 1 Parameters in different stages in building design process, source: [2] ................... 21
Table 2 Stockholmshus standard values .................................................................................... 44
Table 3 Architecture, pros and cons, usability and limitations of EA ...................................... 45
Table 4 Architecture, pros and cons, usability and limitations of Insight ............................... 46
Table 5 Architecture, pros and cons, usability and limitations of GBS .................................. 47
Table 6 Architecture, pros and cons, usability and limitations of EE ...................................... 48
Table 7 Architecture, pros and cons, usability and limitations of EcoDesigner .................... 49
Table 8 Architecture, pros and cons, usability and limitations of Sefaira Systems .............. 50
Table 9 Architecture, pros and cons, usability and limitations of OpenStudio ...................... 51
Table 10 Architecture, pros and cons, usability and limitations of designPH ....................... 52
Table 11 Stockholmshus test results, unit: kWh/m2/year ......................................................... 57
Table 12 ArchiCAD results, unit: kWh/m2/year .......................................................................... 58
Table 13 Sefaira Systems results, unit: kWh/m2/year ............................................................... 58
Table 14 Sefaira Architecture results, unit: kWh/m2/year ......................................................... 59
Table 15 designPH results, unit: kWh/m2/year .......................................................................... 59
Table 16 Weighting system for proposes assessment criteria ................................................ 60
Table 17 Decision matrix of eight CAD program-integrated BES tools ................................. 60
Table 18 Table of comparison of BES tools ............................................................................... 86
Abbreviations and acronyms
nZEB – nearly Zero Energy Building
FTX – Frånluft, Tilluft och Värmeväxling, ventilation with heat recovery
BBR – Boverkets byggregler, Swedish Regulations for building works
BES – Building Energy Simulation
IFC – Industry Foundation Classes
HVAC – Heating, Cooling, and Air Conditioning
IDF – Input Data Format
GBS – Green Building Studio
BIM – Building Information Modelling
AEC – Architecture Engineering Construction
IEA – International Energy Agency
BESTEST – Building Energy Simulation Test
GA – Genetic Algorithm
BEP – Building Energy Performance
LBNL – Lawrence Berkeley National Laboratory
CAD – Computed Aided Design
LASL - Los Alamos Scientific Laboratory
BDA – Building Design Advisor
CFD – Computational Fluid Dynamics
DPV – Design Performance Viewer
NZEB – Net Zero Energy Building
IDA ICE – IDA Indoor Climate Energy
ESBO – Early Stage Building Optimization
EHK – Energihuskalkyl
FEBY – Forum för energieffektiva byggnader
EA – Energy Analysis
EUI – Energy Use Intensity, annual energy consumption divided by gross floor area
PV – Photovoltaic
EE – Energy Evaluation
NREL – National Renewable Energy Laboratory
ASHRAE – American Society of Heating, Refrigerating and Air-Conditioning Engineers
SBA – SmartBuildingAnalyser
EDSL – Environmental Design Solutions Limited
ACH – Air Changes per Hour
WWR – Window-to-wall ratio
ECR – Energy Cost Range
BTU – British Thermal Unit
CFM – Cubic Foot per Minute
SHGC – Solar Heat Gain Coefficient
BFS – Boverkets författningssamling
VAV – Variable Air Volume
DOAS – Dedicated Outdoor Air System
AHU – Air Handling Unit
TFA – Treated Floor Area
FF – Form Factor
R&D – Research & Development
MEP – Mechanical, Electrical, and Plumbing
SBi – Satens Byggeforskningsinstitut
Introduction | 16
Introduction
Background
To achieve national nZEB targets, FTX system with heat recovery efficiency no lower than
75% has become mandatory for all newly constructed buildings in Sweden. The new BBR
drafted in January 2017, has further redefined building energy performance and tightened
the maximum allowed demand level for specific energy. It is therefore necessary to
incorporate these requirements in BES (Building Energy Simulation) tools to accurately
predict future energy performance.
Aim
The present report aims to identify existing energy simulation programs that can intervene
in early-stage of city planning. Such programs should be able to consider relevant building
energy features including climate shell and solar radiation and should be easy-to-use for
architects.
Method
Through screening of available building energy simulation programs on the market, a list
of both national and international tools will be established. The most promising ones will
be tested on a typical Stockholmshus case with standard values in Swedish building
industry. Each tool will then be evaluated with respect to a set of assessment criteria
proposed by involved parties.
The final project deliverables consist in three typical residential building models with basic
inputs including location, geometry, thermal properties and ventilation system. The
models should comply with BBR’s requirements and an additional list of possible
improvements such as better U-values or higher heat recovery efficiency can be proposed
to satisfy Stockholm municipality’s demand.
Limitations
The project was conducted in a relatively short period of time and despite the best effort
made, conclusion have been drawn in the presence of both external and internal limitations.
On the tool side, the inherent structure can prevent it from being thoroughly analyzed; on
the user side, the lack of appropriate expertise (complex energy simulation, programming)
can also lead to unilateral or even superficial understanding of the BES tool.
The project was carried out in a typical Swedish context and is targeted solely at early-stage
building energy simulations. Therefore, the outcomes are mainly valid for the related
climate, building regulation and energy approach and should not be generalized beyond
this scope for the safe of rigor.
17 | Scoping
Scoping
BES theory
The building design process can be fragmented into three stages: outline stage, schematic
stage and detailed stage while each one is characterized by its specific objective, scope, data
availability and quality [2]. As input parameters acquire important documentation from
early to late stage, design modifications have also become difficult and expensive.
The MacLeamy curve (see Fig 1) shows that the pre-design phase has maximum ability to
impact final outcomes and minimum cost of design changes [3]. Comparing to traditional
design process, preferred design process moves the main working load from construction
documentation (CD) phase to schematic design (SD) and design development (DD) phase.
Alternatives are explored before making the decision so that project final outcomes can be
optimized.
Fig 1 The MacLeamy Curve, source: [4]
The need for evaluating design options in the conceptual phase has stimulated the
development of BES tools that operate in a virtual environment. For the past two decades,
BES software have been employed by the professionals to predict and monitor building
energy performance.
Previous studies have classified BES tools into different categories. From a theoretical
approach, Schlueter & Thesseling [5] highlighted the difference between physical
calculation model and statistical calculation model. The former reproduces physical
processes within the building and the latter applies empirically found factors. From a
calculation point-of-view, Tronchin & Fabbri [6] distinguished static method which is
based on real consumption from dynamic method which uses fluctuating parameters for
thermal simulation.
From a practical perspective, Maile et al. [7] separated thermal simulation engines (DOE-
2, EnergyPlus) from their user interfaces (RIUSKA, eQUEST, DesignBuilder, IFC HVAC,
Scoping | 18
IDF Generator and GBS). The user interfaces rely on the same thermodynamics principles
but offer easy access with intuitive inputs and outputs. Their study provided a detailed
review on functionality, life-cycle usage, interoperability and limitations of
abovementioned programs (see Fig 2).
Fig 2 Data exchange capabilities of eQUEST, source: [7]
Most BES tools adopt a post-decision evaluative approach and are intended for use by
engineers and researchers with deep understanding of building technology. In early design
phase, architects need a pre-decision informative tool that provides an indicative energy
consumption rather than accurate quantification of energy loads. They have neither the
time nor the resources to spend on complex preliminary design models.
Hopfe et al. [8] proposed assessment criteria for BES tools regarding program robustness
but Attia et al. [9] stated that architects prioritize intelligence, usability, interoperability
and process adaptability above accuracy and ability to simulate detailed building
components.
In addition, the lack of high-quality data in early-stage has made classic BES tools unusable.
In fact, BES tools often require detailed inputs to maximize customizable options. Jensen
[10] defined high quality data sets to be comprehensive, checked, cleaned, and fully
documented, such dataset can rarely be expected in the conceptual phase. Therefore, a
bespoke decision-aiding simulation tool is necessary to support simple, transparent, and
energy-conscious design.
Performance-based design tools
A performance-based simulation tool generates rapid feedback and is able to point out the
problem area, identify responsible parameters and assess the problem scale [2]. A variety
of these tools have been found in the literature:
Ochoa & Capeluto [11] developed NewFacades, an advice tool that uses EnergyPlus to create
intelligent facades based on energy and visual comfort approach. Urban [12] described MIT
Design Advisor as a simple and rapid energy simulation tool for early-stage building design
purpose.
Petersen & Svendsen [13] confirmed the usability of NewFacades and MIT Design Advisor
as design advice tool together with Building Design Advisor, COMFEN and EnergyPlus
TRNSYS built-in feature for parametric runs. However, the authors pointed out that these
tools failed to provide constructive feedback and designers are forced to repeat design
iterations until reaching a satisfactory performance. They later proposed a performance-
based simulation tool iDbuild to generate design advice through parameter variations.
19 | Scoping
According to Attia et al. [9], the post-design evaluative approach is the main obstacle that
prevents architects from getting adequate support from BES tools. They identified Low,
DesignBuilder, jEPlus and iDbuild as pre-decision informative parametric tools.
Ramsden et al. [3] broadened the list of parametric optimization tools with Sefaira,
ECOTECT, FormIt and Vasari that are primarily aimed at architects. The trade-off between
accessibility and analysis robustness is illustrated in Fig 3:
Fig 3 Existing and desired BES tools, source: [3]
In order to maximize simultaneously usability and precision of energy analysis, the paper
then introduced SmartBuildingAnalyser, a set of components using Grasshopper to
support parametric design in early-stage regarding daylighting and occupant productivity.
From a different angle, performance-based design issues can be addressed through the
implementation of BIM. IFC, developed by the International Alliance for Interoperability
(IAI) and gbXML, developed by Autodesk Green Building Studio are two examples of
exchange file formats. In fact, AEC industry is devoted to promote interoperability between
different actors and IFC standard has rapidly gained popularity for its project management
capability.
According to Azhar et al. [14], BIM represents the building as an integrated database of
coordinated information and its integration with performance simulation tools simplifies
the analysis and gives architects immediate feedback on design alternatives in the
conceptual design stage. Krygiel and Nies [15] indicated that in sustainable design, BIM
can aid to select the best building orientation for reduced energy costs, to analyze building
form, to optimize building envelope, to optimize daylight use, to reduce energy needs and
to analyze renewable energy options such as solar energy.
Program validation
In general, BES programs are subject to various intrinsic limitations: low predictive value
[16], error-prone conversion from geometric model to simulation model [17], complex
process [18], and poor external validity (discrete time-step, deterministic model replacing
continuous, stochastic physical process) [19].
Task 34 of the IEA Solar Heating and Cooling Program performed an empirical validation
of BES tools in the context of innovative low energy buildings. The task created a
comprehensive and integrated suite of BESTEST cases for evaluating, diagnosing, and
correcting BES software [54].
Scoping | 20
The validation methodology can be described as follows: starting from the simplest model
(room without windows), tests are performed on more and more complex models with only
one input parameter changed at a time (see Fig 4). By this way, each model upgrade tests a
specific algorithm.
Fig 4 Validation methodology in BESTEST, source: [20]
However, Hensen & Radošević [21] detected few deviations from BESTEST results. Apart
from implementation and coding errors, they believed that the gap between prediction and
observation can be explained by implicit assumptions and uncommon definitions in the
underlying calculation method. Bazjanac et al. [16] further argued that BES tools employs
deterministic database and are unable to model uncertainty and hazard in building
operation phase. Due to the absence of crucial information in early-stage, arbitrary data are
used to ensure program execution but inevitably lead to arbitrary results. Hence,
calibration is needed to adjust the model to specific building context. Raftery et al. [19]
proposed evidence-based calibration using hourly measured operation data. Such
resources being hardly available in conceptual phase, a bespoke method for model
calibration needs to be de developed.
21 | Screening
Screening
Identification of relevant energy features
A BES tool for conceptual phase focuses on available energy features but in the meantime
reserves possibilities for future optimization. Morbitzer et al. [2] classified parameters that
intervene in different design stages as follows in Table 1.
Table 1 Parameters in different stages in building design process, source: [2]
Outline Stage Schematic Stage Detailed Stage
Orientation (appraisal)
U-values (opaque/
transparent)
Heat recovery systems
Light/heavy construction
Air change rate
(appraisal)
Space usage
Glazing area (appraisal)
Floor plan depth
Fuel type
Glazing area (detailed)
Glazing type
Shading/blinds
Blind control
Orientation (adjusted)
Air change rate
(detailed)
Material adjustment in
overheating areas
Lighting strategy
Heating systems
Heating control
strategies
Cooling systems
(mechanical/free)
Cooling control
strategies
Ventilation
strategies
The most important decisions including building shell, ventilation system and energy
supply tend to be made in the earliest stage of design process. From past experiences,
building energy consumption is essentially determined by its volume, enclosure thermal
properties, airflow, and heat recovery efficiency. Solar energy production potential can
further be deduced from roof area. However, empirical findings need to be scientifically
proven. There are two methods to identify relevant energy features: sensitivity analysis and
optimization.
Sensitivity analysis analyzes parameters with strong repercussion on final energy demand
and establishes the correlation between them. Ourghi et al. [22] studied a commercial
building and proposed a simplified calculation method that incorporates relative
compactness, building type and percentage glazing. The method was found to be accurate
for cooling-dominated climates. Pacheco et al. [23] examined several energy-efficient
structures and found building orientation, shape and the ratio between the external surface
and the volume to be the most sensitive inputs. Hygh et al. [24] used Monte Carlo method
to deduce an approximate equation predicting energy consumption as function of building
form, orientation, fenestration, shading and thermal envelope properties. Tavares &
Martins [25] conducted a case study of a government building in the center region of
Portugal. The most sensitive factors revealed to be: wall type, roofing, shading, air
infiltration, mechanical ventilation, equipment, HVAC, design temperature and thermostat
setpoints. In other literatures, energy features including building length, window-to-wall
ratio [26] and U-values [27] also proved to be relevant.
Optimization consists in testing randomly variable combinations generated by Monte Carlo
method. As the results reach desired outcomes, manipulated variables are likely to be
Screening | 22
predominant in energy analysis. The literature suggests two methods to perform
optimization: genetic algorithm and parametric run.
GA implements the concept of Pareto solution, inspired by the social optimality in
economics. Wang et al. [28] studied floor optimization of a multi-story office building in
Montreal. They varied shape, structure, envelope and overhang characteristics using multi-
objective GA to reduce life-cycle cost and life-cycle environmental impact. Tuhus-Dubrow
& Krarti [29] studied building envelope optimization using GA and DOE-2. Considered
parameters include azimuth, aspect ratio, wall construction, ceiling insulation, thermal
mass, infiltration, foundation insulation, window area, and glazing type.
As for parametric run, Ritter et al. [30] parametrized length, width, height, orientation,
outer skin class, glazing factor to perform real-time feedback on rectangular-shaped office
and administrative buildings. The technique has further been used in software such as
Rhino Grasshopper, Bentley Generative Components and Autodesk DesignScript to
explore tremendous design options. Unfortunately, the method has its limitations. Harding
et al. [31] highlighted that parametric modelling can be highly effective for a known
building type but is unable to explore a wider design pattern in the early design phase.
Despite the individual objective and method of each paper, energy features such as shape,
glazing area and solar radiation are commonly accepted as prevailing. In the scope of the
present report, a list of relevant energy inputs adapted to Swedish territory has been
elaborated:
On location level
Microclimate (solar radiation, shading, wind)
Geographic location
District heating
Orientation
On building level
Aspect ratio
U-values (wall, roof, floor, window)
Air tightness
Thermal bridge
Heat recovery
Airflow
After screening of current BES tools, the list will be narrowed down to suit early-stage data
availability and underlying assumptions in building energy simulation programs.
Description of state-of-the-art BES software
The current chapter describes BES software that have been brought up during literature review and
related research. Some of them have gained popularity regionally or internationally and some might
still remain generally unknown. Each one has been given a short description even no longer available
in few cases. As a whole, they form a panoramic overview of BES software history. To further help
understanding, four sub-categories have been proposed in accordance with development context.
23 | Screening
Thermal simulation engines and derived user interfaces
DOE-2 and EnergyPlus are the two most widely-used simulation engines in BEP analysis.
Both of them are developed by LBNL and stem from a long-time knowledge and expertise
[7].
DOE-2
DOE-2 is devoted to whole building energy performance study during design stage. DOE-
2 combines user inputs with material and construction libraries and computes them into
four programs: LOADS, SYSTEMS, PLANT and ECONOMICS. In relation with weather
data, LOADS calculates heat losses and gains and SYSTEMS determines additional heating
and cooling needs based on temperature setpoints. However, the engine has limited
interoperability and its few variable manipulations are reserved to experienced users [32].
EnergyPlus
EnergyPlus integrates heat and thermal mass balance in building system simulation to
provide more accurate and reliable results. EnergyPlus imports inputs from text file and
exchanges data through IFC. EnergyPlus supports a wide range of advanced modules
including TRNSYS but does not provide any graphical interface itself. The engine is suitable
to all building life-cycle phases [33].
RIUSKA (DOE-2 engine)
RIUSKA is developed by Olof Granlund in 1996 aiming at the whole building process. The
tool imports building geometry through IFC and requires additional inputs including
location, space types, thermal zones and air conditioning systems. Construction types
(layers, material types and thickness) are not extracted from CAD models and need to be
manually assigned in RIUSKA default database. Space types (temperature set-points,
internal loads) are predefined in RIUSKA based on energy codes and user experiences but
are modifiable on demand. RIUSKA allows creation of different alternatives from the base
case. RIUSKA adopts floor-based view for imported geometries and is the most compatible
with Granlund’s own CAD software SMOG.
eQUEST (DOE-2.2 engine)
eQUEST provides two design wizards: Schematic Design Wizard (SDW) and Design
Development Wizards (DDW) that differ significantly in detailing level. eQUEST performs
rapid comparisons of specific input parameters to propose energy saving measures. As for
interoperability, eQUEST enables building geometry import via DWG or gbXML but both
paths require cumbersome manipulation to adjust the model. SDW is further limited to one
building footprint [34].
Screening | 24
Fig 5 Predefined shape in eQUEST (3D view under Detailed Interface), source: [34]
Fig 6 Simulation results in eQUEST, source: [34]
Building Design Advisor (BDA) (DOE-2 engine)
BDA, developed by LBNL, contains a schematic graphic editor to define geometry and room
functions. The construction of a building involves step by step: create a new story, draw
space, add external obstruction (shadings) and window, add overhang or vertical fin to
window, add luminaries to space, and change building azimuth [35]. As for results, BDA
uses a graphical interface, Design Decision Desktop, to compare the performance of design
alternatives with respect to multiple parameters. Parameters can themselves refer to
project, plants or rooms. However, BDA is limited to three building types (lodging, office
and restaurant) located in the US or Canada and appears to suffer from recurrent instability.
Fig 7 3D isometric view in BDA
Fig 8 Result visualization in BDA
DesignBuilder (EnergyPlus engine)
DesignBuilder is the most comprehensive and easy-to-use interface for EnergyPlus. The
tools allows both internal creation of building geometry and import from DXF files.
25 | Screening
DesignBuilder provides country or region-specific templates for a wide range of parameters
but enable customization of heating and cooling systems. DesignBuilder has an
optimization feature and can validate building thermal models against local energy codes.
DesignBuilder is adapted to all phases of design process and performs simulations of
energy, CFD, daylighting, cost and carbon. Its typical energy outputs include total energy,
electric load, on-site thermal sources (heat recovery, geothermal, solar) and water sources.
DesignBuilder generates a full analysis report exportable to PDF format [36].
Fig 9 Editing window in DesignBuilder
Fig 10 Temperature and thermal simulation in DesignBuilder
Simergy (EnergyPlus engine)
Simergy is a graphical user interface designed for early stage purpose. The building
geometry can be extruded vertically from floor plans or imported from BIM. Simergy
provides six predefined building shapes (rectangular, L-shape, H-shape, cross-shape, U-
shape and T-shape) but offers the possibility to draw free forms in an integrated CAD
interface. Simergy contains libraries for materials, construction and HVAC components.
However, Simergy is incapable of modelling several buildings and is limited to the United
States in terms of location and units [37].
Fig 11 Extrusion and stacking of standard floor plan shapes, source: [38]
Screening | 26
Fig 12 Outputs of whole building performance in Simergy, source: [38]
Design Performance Viewer (DPV) (EnergyPlus engine)
DPV is a prototypical performance-based simulation tool developed by Schlueter &
Thesseling [5] at ETH Zürich to integrate energy calculations into BIM. DPV enables fast
and holistic building energy analysis and has been employed in several international case
studies. As an add-in to Revit 2014, it performs dynamic simulation and displays energy
consumption and CO2 emissions [39].
The use of DPV requires semantically correct element types, i.e. components must be
defined with the dedicated tools. The simulation is performed on a wire-framed model as
shown in Fig 13. DPV replaces the neighboring buildings by mass objects but is incapable
of simulating multiple buildings at the same time.
Fig 13 Wire-framed simulation geometry in DPV, source: [40]
Fig 14 Energy balance breakdown in RevitPythonShell, source: [40]
ZEBO
ZEBO is an energy simulation tool developed by Shady Attia at Université catholique de
Louvain to inform architects about the sensitivity of each parameter and to achieve NZEB
target. Its inputs include building type, climate, geometry, envelope and photovoltaic
system. ZEBO incorporates an alternative comparison feature [9].
27 | Screening
Fig 15 Output window in ZEBO, source: [9]
In Nordic countries
The following section presents the tools developed in Nordic countries that are particularly
adapted to the specific climate (heating-dominated) and local energy codes [41].
BSim ([57])
BSim is a building simulation tool developed by Danish Building Research Institute in
2000 aiming at high energy efficiency and optimal daylight use. The program package
includes a graphical user interface to create and define building geometry, constructions,
materials and installations but also has a module to import plan drawings in DXF format.
BSim adopts multi-zone approach which takes into account heat and mass transport
between neighboring thermal zones. Result categories range from energy use, solar
radiation, illuminance to moisture balance. BSim is further validated by IEA Task 12 -
Empirical validation of thermal simulation programs using test room data [42].
Fig 16 CAD interface in BSim, source: [42]
Fig 17 Sunlight and shadow visualization in BSim, source: [42]
Screening | 28
BV2-arch
BV2-arch is an architect-aimed tool dedicated to early-stage design purpose. Based on the
energy analysis program BV2, the tool is able to process incomplete dataset, especially with
missing technical installations. As an exchange platform, BV2-arch first allows the client to
lock in chosen parameters such as project location and then invites architects to modify the
remaining inputs, typically building shape, glazing percentage and solar panel.
Users can customize general properties to buildings (percentage glazing, axial coordinates
and orientation) and component-relate inputs (construction type, U-value or external
shading). BV2-arch uses an integrated CAD interface to draw 2D geometries and generates
a 3D model view. Program computes energy balance per unit area for three scenarios (day,
night, maximum) and can compare design alternatives from an energy perspective [43].
Fig 18 CAD interface in BV2-arch
Fig 19 Energy balance calculations in BV2-arch
IDA Indoor Climate and Energy (IDA ICE)
IDA ICE is a general simulation program developed by Swedish company EQUA Simulation
AB. Similar to BSim, IDA adopts multi-zone approach and contains three levels of model
complexity: wizard level defines building and room properties; standard level refines
geometry, materials, controllers and loads; and advanced level establishes algorithmically
component connections. Typical outputs include energy use, indoor climate, moisture
balance, cost, and daylight calculations. IDA is validated by IEA Task 12 - Envelope
BESTEST [44].
Fig 20 General tab in IDA ICE at standard level, source: [44]
29 | Screening
Fig 21 Schematic tab in IDA ICE at advanced level, source: [44]
Fig 22 Total heating and cooling simulation plots in IDA ICE, source: [44]
IDA Early Stage Building Optimization (ESBO)
ESBO is a simulation program for building design optimization. It adopts single-zone
approach and is assimilate to wizard level in IDA ICE. Users can define room-relative
parameters (type, floor area) and building-relative parameters (location, ventilation system,
domestic hot water consumption, infiltration rate). The output is whole year energy
simulation [45]. ESBO is adapted to early-stage design purpose and uses shading objects
to model adjacent buildings at district level.
Fig 23 Building tab for primary systems in ESBO, source: [36]
Fig 24 Room tab for secondary systems in ESBO, source: [36]
Screening | 30
Fig 25 Result tab in ESBO, source: [36]
VIP-Energy
VIP-Energy is a software developed by StruSoft AB to calculate building energy
performance. VIP imports building geometries from ArchiCAD and can refine inputs
including climate data, dimensions, construction types, schedules and ventilation. VIP can
be used for all building types and contains an integrated database for materials, building
components and plants. As for outcomes, VIP displays energy balance, norm (BBR,
ASHRAE 90.1 and LEED) comparison and costs [46].
VIP runs hourly annual simulation within a few seconds and its accurate model can be used
for passive house design. VIP is validated by IEA-BESTEST [47].
Fig 26 Building-related parameters input window, source: [46]
Fig 27 Energy balance in VIP, source: [46]
Energihuskalkyl (EHK)
EHK is an online program that calculates heat losses, purchased energy and delivered
energy for buildings. EHK refers to Swedish building norms including BBR and FEBY 12.
EHK supports municipality’s tendering-bidding process by offering a normative method to
estimate building energy performance [48]. Typical inputs include dimensional properties
of climate shell, thermal bridges and glazing [49]. However, EHK is based on theoretical
thermodynamics principles and does not allow model visualization.
31 | Screening
Fig 28 EHK calculation sheet for single-family house, source: [49]
Fig 29 Result summary, source: [49]
Derob-LTH
Derob is a design tool initiated at University of Texas and developed at Lund University.
The tool can simulate a wide range of building types and is targeted at students, researchers,
architects and energy consultants. Derob uses dynamic calculations to determine building
energy performances including energy use and peak loads for heating and cooling, thermal
and visual comfort. It contains libraries for materials and constructions for roofs, walls,
floors, doors and windows [50] but site data, building geometry and room schedules
needed to be manually assigned. Surfaces are located using their coordinates but can later
be visualized in a 3D view. Derob requires further a license for educational and research
purposes.
Fig 30 Creation of building elements in Derob, source: [50]
Fig 31 Thermal comfort results in Derob, source: [50]
HAM-Tools
HAM is a whole building simulation tool developed at Chalmers University of Technology.
Its main objective is to simulate heat, air and moisture transfer processes in the building.
In particular, HAM analyses energy consumption for heating and cooling, indoor comfort,
risk of high moisture content level, functionality of HVAC systems and air flow distribution
Screening | 32
through openings [51]. HAM relies on Simulink models and is part of IPBT-2 (International
Building Physics Toolbox) open-source package.
Fig 32 Simulink model in HAM-Tools, source: [52]
Fig 33 Annual energy consumption for heating and cooling, source: [51]
Energy10
Energy10 is an online service developed by Energy Systems A/S in Denmark for energy and
environment analysis. Energy10 uses standard templates to define building geometry but
allows editing of envelope and building-specific input data. The program computes energy
demand, heat supply and electricity demand per end-use and electricity production (solar,
wind). The results are further compared to a reference building prescribed by Danish
Building Regulations 2010 [53].
Fig 34 Window-related parameters in Energy-10, source: [53]
Fig 35 Energy labels in Energy-10, source: [53]
33 | Screening
CAD program-integrated tools
To better meet with AEC industry’s increasing need for sustainable design, many software
companies have committed significant effort to integrate energy analysis in CAD
environment. The following section shows four mainstream CAD programs and their
various energy plug-ins.
Autodesk family
Ecotect
Ecotect has been discontinued by Autodesk in 2015 to promote integrated tools for energy
efficiency and high performance design. Its key solutions are now available in Revit
environment (Lighting Analysis, 360 Rendering, Energy Analysis and FormIt).
Fig 36 Sun path and shadow visualization in Ecotect, source: [54]
Vasari
Vasari is a building performance analysis tool for conceptual modelling. Its analyzing
objects include wind, climate, daylighting and electric lighting, whole building energy and
solar. The service is permanently closed but its main features can be found in FormIt,
Dynamo and Revit.
Fig 37 Solar radiation in Vasari, source: [55]
Energy Analysis for Revit
Energy Analysis (EA) is a built-in feature for Revit 2016. It creates energy models from
conceptual masses in early stage and from building elements in late stage. EA uploads
energy model to Green Building Studio in the backstage and generates an energy report
highlighting EUI, life-cycle energy cost and renewables potential (cf. Annex A). In fact, the
Screening | 34
DOE-2 based simulation engine GBS performs comprehensive BEP analyses and powers
all Autodesk energy simulation tools.
Fig 38 3D energy model in Revit for a single-family housing model
Insight for FormIt and Revit
Insight provides add-ons for both FormIt Pro and Revit 2016 and has a cloud-based
interface to facilitate manipulation.
Autodesk FormIt is an early stage-targeted design tool. It enables simple building volume
creation and can export to Revit for detailed modelling. It can further convert Revit families
or SketchUp warehouse into its own content library. Insight plug-in for FormIt requires
project to be located and at least one solid object to be applied with level before running
simulation.
Fig 39 FormIt web application interface
Apart from energy performance, Insight provides lighting and solar analyses and relies on
EnergyPlus for heating and cooling loads calculation. It also allows visualization of loads
and PV panels.
Fig 40 Heating loads visualization in Insight
Green Building Studio (DOE-2 engine)
Green Building Studio is the simulation engine used by all Autodesk energy analysis
applications and provides an online interface. GBS project-specific settings include space
use, facility power density, thermal zone setpoint, construction type and HVAC equipment.
35 | Screening
Most of them are either commonly used in industry or prescribed by building regulations
such as ASHRAE 90.1.
GBS checks automatically conversion errors and displays as outputs building energy,
resource use, carbon emission and costs. Though it requires little preparative work, GBS
has a predetermined analysis type and is unable to handle large files. The same single-
family housing model is uploaded to GBS through gbXML export and its simulation charts
is shown below. Furthermore, GBS estimates energy production potentials for photovoltaic
and wind power and has a beta feature of evaluating potential energy savings based on
insulation type, equipment efficiency, control strategies, orientation and infiltration rate.
GBS can export to EnergyPlus and eQUEST [56].
Fig 41 Simulation charts in GBS
ArchiCAD
Energy Evaluation (EE) (VIP-Energy engine)
Energy Evaluation is an in-built feature of Graphisoft ArchiCAD. Based on VIP-Energy, the
energy analysis of building model requires correct definition of thermal zones with borders,
structure and schedules. The results are presented in the form of an energy report
containing key values, energy consumption, energy balance and environmental impacts (cf.
Annex B).
Fig 42 A single-family dwelling model in ArchiCAD
EcoDesigner Star (VIP-Energy engine)
EcoDesigner is an extension for ArchiCAD based on the same workflow as Energy
Evaluation. In addition to EE features, EcoDesigner is able to comply the model with
Screening | 36
standards (ASHRAE 90.1, LEED Energy), to perform thermal bridge simulations, to assess
on-site renewables (solar photovoltaic, wind power) and to compare the results with
baseline performance.
Although Energy Evaluation seems to possess some functionalities claiming exclusive to
EcoDesigner (multiple climate zones, operation data editing), EcoDesigner is undeniably
an updated version of EE.
Third-party plug-ins
Sefaira Architecture for Revit and SketchUp (EnergyPlus engine)
Sefaira Architecture is an easy-to-use performance-based simulation tool. It calculates
energy use intensity, energy segments, i.e. the distribution between different end-uses, and
daylighting. Sefaira Architecture operates as a plug-in to Revit and SketchUp and has a
web-based program called Sefaira Systems. While the in-app plug-in has an intuitive and
simple user interface, the online service enables detailed analysis and design alternative
comparison. Both Sefaira applications provide nearly real-time feedback on energy
performance and are able to model a building group. Users can apply predefined building
properties according to common standards such as ASHRAE 90.1 but can also create and
save their own settings. Sefaira energy analysis view for a single-faming housing model and
its simulation results are respectively shown in Fig 43 and Fig 44.
Fig 43 Sefaira energy analysis view in Revit
Fig 44 Sefaira energy and daylight analysis results in Revit
37 | Screening
IES Virtual Environment (VE) for SketchUp
IES VE plug-in for SketchUp identifies automatically rooms in the model and allows users
to define building-related inputs such as location, usage and construction type. The plug-
in then exports the massing geometry to VE-Ware program for energy analysis [57].
VE-Ware assesses the availability of wind, solar and rain resources and monitors water use
at the site. It evaluates daylight impact, shading and sunshine penetration and performs
whole building energy and carbon analysis. VE-Ware can further comply the results with
rating systems (LEED, Green Star, BREEAM) and regulations (UK Part L2A 2010,
ASHRAE 90.1, Architecture 2030 Challenge).
Fig 45 VE SketchUp plug-in showing room construction types
Fig 46 System loads in VE-Ware, source: [57]
OpenStudio for SketchUp
OpenStudio is a cross-platform (Windows, Mac, and Linux) collection of software tools to
support whole building energy modeling using EnergyPlus and advanced daylight analysis
using Radiance. OpenStudio has four graphical applications: OpenStudio SketchUp Plug-
in, OpenStudio Application, ResultsViewer and Parametric Analysis Tool (PAT).
OpenStudio SketchUp plug-in quickly creates geometry needed for energy simulation by
adding space types and thermal zones to existing model [58]. The building envelope is then
exported to OpenStudio Application to be completed with weather file, design day file,
construction types, space schedules and zone equipment [59]. Typical outputs include
energy use, energy cost, and renewable energy source. The application further compares
the results with Standard 62.1 (indoor air quality) and LEED rating system.
Screening | 38
Fig 47 OpenStudio rendering by thermal zones in SketchUp
Fig 48 Variable plot (site outdoor air wet bulb temperature) in ResultViewer
designPH for SketchUp
designPH is the new, interactive and graphically oriented input interface developed by the
Passive House Institute for PHPP (Passive House Planning Package). designPH SketchUp
plug-in provides preliminary results based on simple energy balance and can export the
model to PHPP for a full analysis. Instead of manually entering model properties as in
PHPP, designPH automatically recognizes temperature zones and building elements but
users can refine surface construction material and area groups. As an iterative design tool,
designPH allows optimization of building design and facilitates integration with passive
house objective [60]. The output includes annual heat demand, internal and solar heat
gains, and heat losses via transmission and ventilation.
Fig 49 Workflows in designPH and PHPP, source: [60]
Rhinoceros 3D
Grasshopper and Ladybug Tools
Grasshopper is a graphical algorithm editor for Rhino; Ladybug and Honeybee are two
open source environmental plug-ins for Grasshopper. Honeybee connects Grasshopper to
EnergyPlus for energy simulation and to Radiance for daylighting analysis [61]. Honeybee
is recognized among professionals for parametric design of topological objects and it
supports district level modelling in an optimization perspective.
39 | Screening
Rousdari [62] described a case of energy and lighting optimization using Rhino
Grasshopper, Matlab, EnergyPlus and Radiance. In his example, Grasshopper is used as
the main interface for building the architectural geometry; Radiance and EnergyPlus for
evaluating daylighting, heating and cooling loads; and Matlab for executing simulations
and comparing each option to defined objectives.
Fig 50 Grasshopper, Matlab, EnergyPlus and Radiance coupling, source: [62]
Furthermore, University of Bath developed SmartBuildingAnalyser (SBA) that relies on
Grasshopper to rapidly analyze design options and to explore decision flexibility in early
stage of building process. While the concept of multi-goal optimization is interesting, SBA
is mainly aimed at engineers with a deep understanding of building technology [3].
Other software
ESP-r
ESP-r is a modelling tool for building performance simulation. The objective of ESP-r is to
simulate building performance in a realistic way and to support early-through-detailed
design stage decisions. The software provides an in-built CAD interface to define geometry
and can add to the model shading and insolation patterns, radiation factor, facade-
integrated photovoltaic modules, temperature dependent thermal properties and CFD
domains. ESP-r contains a database for surface and space related entities [63].
Fig 51 Model viewing and result analysis in ESP-r, source: [63]
MIT Design Advisor
The tool is a web-based service developed at Massachusetts Institute of Technology (MIT)
to address early stage design issues. MIT Design Advisor aims to conceptualize, simulate
and analyze building design rapidly with respect to energy consumption. Basic inputs
include project location, building dimensions, room orientation, window and wall type,
occupant load and ventilation system. The tool further allows the comparison of up to four
design alternatives [12].
Screening | 40
Fig 52 Typical room properties in MIT Design Advisor
Fig 53 Monthly energy use for heating, cooling and lighting, source: [12]
Tas (Thermal Analysis Simulation)
Tas is an industry-leading building modeling and simulation tool. Capable of performing
dynamic thermal simulation for the world’s largest and most complex buildings, Tas allows
designers to accurately predict energy consumption, CO2 emissions, operating costs and
occupant comfort [64]. Tas contains a comprehensive database for construction materials
and glazing types. Tas defines building geometry by internal drawing or import from CAD
files and can generate a shading rendering. Tas enables result visualization and computes
control strategies.
Fig 54 3D Modeller in Tas, source: [64]
Fig 55 Results Viewer in Tas, source: [64]
41 | Screening
ECOCITIES
ECOCITIES is a software developed by XYLEM Technologies for energy optimization of
building portfolios under 2012 European Energy Efficiency Directive. ECOCITIES
calculates all energy and cost-efficient development scenarios and allows decision makers
to visualize the political, economic and environmental consequences of their actions.
ECOCITIES considers energy-efficient building configurations, gray energy,
environmental impact, financial constraints, legal constraints (building codes), operation
energy consumption, renewable energy production (solar PV), energy network (district
heating) and local typology [65].
Fig 56 Web-based building portfolio, source: [65]
Fig 57 Scenario analysis and energy optimization, source: [65]
iDbuild
iDbuild is developed by Aarhus University and Technical University of Denmark to
facilitate systematic parameter variations. The tool is programmed in Matlab and takes as
inputs room geometry (dimensions and orientation), construction properties (thermal,
solar and visual), internal loads, lighting, ventilation, thermal zones and photovoltaics [13].
Fig 58 Result of parameter variation, source: [13]
Screening | 42
Assessment criteria User-friendliness, the indisputable priority for architects in conceptual design stage, can be
expressed by following criteria:
Adapted inputs options: 3D/2D geometry, relevant energy features identified in §3.1
Reliability of calculation method
Similar development context to Sweden: energy terminology, simulation approach,
building regulations
Small need of prerequisites: basic CAD drawing skills, no experiences with energy
simulation required
Process simplicity
Usability in early-stage (to facilitate future optimization, usability throughout the
design process can be a benefit)
Reasonable license option
Graphical presentation of results
An evaluation of abovementioned tools with respect to proposed criteria is summarized in
a comparative table (cf. Annex D).
43 | Selection
Selection
The main functionality of an early-stage suitable BES tool is to calculate energy
consumption for a given building with well-defined geometry, site location and standard
values for relevant energy inputs.
The program should allow customization of following inputs:
Weather conditions
Building outer shell thermal properties
Window solar transmittance factors
Airflow
Heat recovery
Indoor temperature
Air leakage
As for outputs, the program should generate:
Heating demand or energy consumption per end-use
Solar energy production potential (deducible from roof area)
Results compliance with Swedish building code
In fact, Stockholm municipality has defaults values for hot tap water, fans, pumps and
tenant electricity (70% of which contribute to internal heat gain) so that energy
consumption can be easily obtained from heating demand.
In the specific context of the project, CAD program-integrated tools seem the most
promising as they construct internally energy models and avoid time-consuming and error-
prone geometry rebuild in stand-alone energy applications. Three mainstream CAD
programs and their respective energy plug-ins have been thus selected to be thoroughly
examined:
Autodesk Revit in-app features Energy Analysis and Insight, both powered by Autodesk
energy simulation engine Green Building Studio
Graphisoft ArchiCAD add-ons Energy Evaluation and EcoDesigner
SketchUp third-party plug-ins Sefaira Architecture, OpenStudio and designPH
Test | 44
Test
Stockholmshus case
Previously selected BES tools are now submitted to a demonstrational test with standard
values used at Stockholms Stadsplanering office (see Table 2).
Table 2 Stockholmshus standard values
U-values
Ground slab 0.2 W/m2K
Wall 0.15 W/m2K
Window 0.9 W/m2K
Roof 0.1 W/m2K
Floor 0.25 W/m2K
Door 1 W/m2K
Air leakage at 50 Pa
Wall/Roof 0.6 L/ m2s
Window/Door 0.8 L/ m2s
Ground slab 0.1 L/m2s
Solar transmittance factor Direct 50%
Total 55%
Ventilation
Airflow per person 10.5 L/s/person
Airflow per area 0.35 L/m2s
Air changes per hour
(ACH) 0.5
Heat recovery efficiency 80%
Temperature setpoints1 Heating 20°C
Cooling 25°C
Tenant electricity Equipment 1 W/m2
Lighting 1.5 W/m2 1: If not specified for heating or cooling, 21°C is applied
An IFC file of a multi-story residential building is provided by Familjebostäder for the
Stockholmshus test. The model locates in Stockholms län and is used as geometry input in
all programs. In fact, as an exchange format for BIM, IFC minimizes information loss,
redundancy and error when importing or exporting in different platforms. All chosen CAD
programs (Revit, ArchiCAD and SketchUp) are compatible with IFC standard so that
functionalities of each tool can be assessed with respect to the same model.
Ideally, the program can provide (nearly) real-time feedback for energy performance based
on model changes. That is to say, users should be able to modify building form, orientation,
number of stories and window-to-wall ratio with ease.
In the following section, each tool is provided with a table summarizing findings about its
architecture, pros and cons, usability and limitations.
Revit
All energy analysis performed in Autodesk applications have a mother project in Green
Building Studio. In Energy Analysis for Revit 2016 or older versions, it is possible to choose
45 | Test
a particular GBS project in which simulations will be carried out. In Revit 2017 and later
versions, Energy Analysis is replaced with Energy Optimization which is assimilated to
Insight. They are no longer capable to run simulations with GBS project-specific settings.
Energy Analysis
Energy Analysis (EA) is a built-in feature for Revit 2016. Its energy settings contain
customizable options from location, project phase, analytical resolutions and building type
to operating schedule, HVAC system and outdoor air information. Users can override
construction types with explicit U-values or otherwise assembly thermal properties will
apply. It is further possible to define a target glazing percentage (default set to 40%) but it
is unclear how the program computes the value. A detailed workflow can be found in §12.1.
Table 3 summarizes the findings about EA.
Table 3 Architecture, pros and cons, usability and limitations of EA
Inputs Architectural model
Location
Analytical model characteristics
Target percentage glazing
Building type
Operating schedule
HVAC system
Outdoor air information
Schematic types (explicit U-values)
Outputs Number of occupants
WWR
EUI
Renewable energy potential (scenarios from low to high PV
efficiencies)
Monthly heating and cooling loads
Pros Simple to use
Free-of-charge for Autodesk subscribers
Model viewing
Graphical results
Easy to orientate project
Cons Internet connection required
Program instability (unknown running errors)
Result inconsistency (floor area different GBS)
Difficult to assign exact U-values
Complex design modifications (add a story, change aspect ratio)
Simulation
assumptions
Default occupant density (living area per person)
Design temperatures 22.2°C for heating and 23.3 °C for cooling
Running time Minutes to hours depending on model complexity
Documentation Revit online guide
Test | 46
Insight
The Revit plug-in applies either Insight defaults or Revit Energy Settings depending on
export categories. However, deviations have been observed between Insight and GBS
results and no infallible explanation has been yet deduced.
The in-app window displays 3D model view, EUI and Energy Cost Range (ECR). It further
incorporates individual widgets for energy factors showing their correlation to building
performance so that users can quickly construct alternative scenarios. Insight enables
comparison between models, Net Zero standard and Architecture 2030 (carbon neutral)
Challenge. A detailed workflow can be found in §12.2. Table 4 summarizes Insight’s new
features compared to EA.
Table 4 Architecture, pros and cons, usability and limitations of Insight
Inputs Architectural model
Revit Energy Settings or Insight defaults
Outputs ECR/EUI
Sensitivity analysis of a wide range of parameters (orientation,
WWR, shading, construction type, infiltration rate, daylighting
and occupancy control, HVAC system, schedules and solar panel
efficiency)
Scenario comparison
Heating and cooling loads with visualization
Lighting and solar analysis
Visualization of heating and cooling loads
Visualization of PV panels
Pros Interactive in-app window
Internal creation of design alternatives based on energy factors
Cons Program instability (heating and cooling loads)
Result inconsistency (EUI different from GBS)
Model viewing incongruity (missing building parts)
Simulation
assumptions
Default occupant density (living area per person)
Design temperatures 22.2°C for heating and 23.3 °C for cooling
Running time Minutes to hours depending on model complexity
Documentation Autodesk user forum
Remarks Notification of simulation progress via email
Different from Revit built-in feature Heating and Cooling Loads
Green Building Studio (GBS)
GBS processes gbXML files (exportable from Revit) and computes a series of alternative
runs varying WWR, orientation, construction, infiltration, lighting efficiency, occupancy
control, HVAC type, operating schedule and internal loads. It compares all results with the
base run so that the alternative with the best performance metrics can be quickly identified.
A detailed workflow can be found in §12.3. Table 5 summarizes the findings about GBS.
47 | Test
Table 5 Architecture, pros and cons, usability and limitations of GBS
Inputs Revit energy model or exported gbXML file
Spaces properties
Zones properties
Surface types (implicit U-values)
Openings types
HVAC equipment
Outputs Both energy and cost results
Comparison of alternative runs to base run and sorting by
performance metrics
Internal creation of scenarios based on parametrized energy
features
Review of simulation assumptions (hydronic and air equipment)
Pros Little preparative work
Free-of-charge for Autodesk subscribers
Graphical results
Exhaustive list for surface constructions and HVAC equipment
Optimization based on parametrization (orientation, WWR)
Cons Unknown units for annual data
Complex external design modification in Revit (add a story,
change aspect ratio)
Internet connection required
Model viewing unavailable
Implicit U-values for surface constructions
Restrained library for opening components
Imperial units only (feet, BTU, Fahrenheit, CFM)
Running time Minutes to hours depending on model complexity
Documentation Revit building performance analysis online help
Remarks Project-specific settings cannot be reviewed after submission of a
run
By default, base run results are located at the top of annual data
bar chart
Building systems in compliance with American standards (Title
24, ASHRAE)
Result rating by certification systems (EPA Energy Star, LEED
Daylight)
It is unclear how GBS reacts when Revit Energy Setting and its
own project defaults are in conflict
ArchiCAD
ArchiCAD is a highly BIM-compatible program and can convert IFC components to its
embedded library. To create an energy model, zones need to be added with respect to floor
Test | 48
plans. In Energy Model Review dialog, users can define thermal blocks with operating
schedules and HVAC systems that are later customizable in Simulation Options. After
zones have been affiliated to thermal blocks, ArchiCAD identifies automatically the exterior
and interior surfaces (walls, slabs, floors, roofs) and openings. Elements from the same
area group can be assembled to facilitate properties editing (U-value, infiltration, g-value).
Energy Evaluation (EE)
EE, the basic version of energy simulation in ArchiCAD, is ready to run after correct
assigning of zones and thermal blocks. A detailed workflow can be found in §13.1. Table 6
summarizes the findings about EE.
Table 6 Architecture, pros and cons, usability and limitations of EE
Inputs Climate file or project location
Zones (footprint, volume)
Thermal blocks
Building systems (heating, cooling, ventilation)
Operation profiles (occupancy data, daily profiles)
Surrounding environment (soil type, horizontal shading)
Structure properties (U-value)
Opening properties (U-value, SHGC)
Outputs Building envelope average U-value
Net heating and cooling energy
Energy consumption
Infiltration at 50 Pa
WWR
Pros Adapted to Swedish territory
Numerous input options
Simple to use
Model viewing
3D component visualization
Customizable report (content and style)
Graphical results
Easy to orientate project
Short running time (~seconds) regardless of model complexity
Cons Requires good skills in ArchiCAD
Unknown default heat recovery efficiency
Complex in-app design modifications (add a story, change aspect
ratio or WWR)
Unusual percentage of opaque surface for window components
and derived unrealistic WWR
Running time Within a few seconds
Documentation Energy Evaluation workflow overview (online)
49 | Test
EcoDesigner
EcoDesigner is the expert version of energy simulation in ArchiCAD. While EE contains
limited input options for building systems, EcoDesigner provides detailed data on them
such as heat recovery characteristics. Apart from EE outputs, EcoDesigner also calculates
solar energy production and can export energy results in the form of a spreadsheet to
compare with BBR requirement categories. A detailed workflow can be found in §13.2.
Table 7 summarizes new features of EcoDesigner compared to EE.
Table 7 Architecture, pros and cons, usability and limitations of EcoDesigner
Inputs Extra options for building systems (solar panel characteristics,
heat recovery efficiency)
Reference building for benchmark comparison
Outputs On-site renewables (solar photovoltaic, wind energy)
Comparison with BBR (specific energy use, average U-value, heat
gain from electricity)
Pros Compliance with BBR 22 and BFS 2015:3)
Detailed and customizable report
Cons ArchiCAD restart indispensable for the upgraded version to be
effective
Running time Within a few seconds
Documentation EcoDesigner Star User Manual
SketchUp
Energy simulation in SketchUp requires strictly conceptual model, i.e. simple geometry
with thin planes. Direct IFC conversion being over complex, a simplified model is built with
reproduced positions and dimensions of building parts but rooms of the same story merged.
Although the simplification is inevitably subject to underlying assumptions, the new model
proves to be nearly identical to the original one from the energy perspective (see §8).
Sefaira Systems
While Sefaira Architecture plug-in is penalized by limited input parameters (U-values,
SHGC, infiltration and ventilation rate, lighting and equipment power density), users can
upload the model to the online server Sefaira Systems for an in-depth customization
including shading device, space properties and solar photovoltaic. A detailed workflow can
be found in §14.1. Table 8 summarizes the findings about Sefaira.
Test | 50
Table 8 Architecture, pros and cons, usability and limitations of Sefaira Systems
Inputs Location
HVAC system to choose between VAV and DOAS
Envelope properties (U-values, infiltration)
Shading device (horizontal, vertical, automated blinds and
shades)
Space use (occupant density, lighting and equipment power
density, airflow, design temperatures, operating schedule for
HVAC systems and internal loads
Solar photovoltaic characteristics
Outputs AHU design airflow
Renewable energy production
Energy costs
Energy breakdown per end-use (heating, cooling, fans, pumps,
lighting and equipment)
Carbon emissions
Peak loads
Comfort level expressed in unmet hours
Pros Automatic recognition of surface area groups
Nearly real-time feedback based on model changes
Possible to override orientation and WWR
Cons Limited choices for HVAC system
Internet connection required
Same construction set and HVAC system applied to the building
External design modification in SketchUp (add a story, change
aspect ratio)
Lower limit of typical U-value range: 0.1 W/m2K
Unknown calculation method for tenant electricity
Running time Within a few minutes
Documentation Online tutorials
Remarks Only Sefaira plug-ins for SketchUp allows refining of surface tag
Complies with LEED, BREEAM and Title 24
US terminology (unit area, energy segment)
Sefaira interface contains deliberately limited input options
User-defined envelope properties in Sefaira Architecture can be
reloaded in Sefaira Systems
User-defined space use settings can be saved in Sefaira Systems
User-defined space use settings can be saved
Sefaira Systems allows simultaneous editing of three airflows in
convertible units but the calculation method is unknown
51 | Test
OpenStudio
OpenStudio Application offers great customization possibilities for building features from
schedule, constriction and load to space, facility and HVAC system. However, its predefined
inputs are not transparent and the program is mainly intended for office buildings.
Furthermore, OpenStudio suffers from persistent instability and the attempt to generate
meaningful results was not successful under the test period. A detailed workflow can be
found in §14.2. Table 9 summarizes the findings about OpenStudio.
Table 9 Architecture, pros and cons, usability and limitations of OpenStudio
Inputs Weather file
Design day file
Construction types
Space schedules
Zone equipment
Outputs Energy use
Energy cost
Renewable energy source
Compliance with Standard 62.1 (indoor air quality) and LEED
Pros Detailed customization
Continuous tool development
Cons Predefined inputs not transparent
Rigid tool architecture
Predominantly for office buildings
Program instability
Additional work to rebuild model using OpenStudio integrated
tools
Running time Simulation failed
Documentation Online tutorials on GitHub
Remarks OpenStudio mainly complied with American standards
OpenStudio is a cross-platform tool targeted at developers and
engineers with programming skill
designPH
designPH extracts automatically Area Group (door, wall, roof and slab) and Treated Floor
Area (TFA) from SketchUp model but allows to refine them for more accurate calculations.
designPH integrates a list of surface constructions with U-values but users can create their
own assemblies which are simultaneously added to the list. designPH can render the model
by area group or component to quickly identify unassigned surfaces. In addition, users can
check model thermal properties with Face Info Tool. designPH generates instant
simulation results that comprise important performance metrics and heat balance
breakdown. A detailed workflow can be found in §14.3. Table 10 summarizes the findings
about Sefaira.
Test | 52
Table 10 Architecture, pros and cons, usability and limitations of designPH
Inputs Geographic location (country then city)
User-defined assemblies (U-value, thickness)
User-defined frame and glazing types (U-value, g-value)
U-values (predefined components or customized assemblies)
Outputs Surface rendering by area group or component
Annual heat demand
Treated floor area
Thermal envelope area
Heat losses (through transmission and ventilation)
Heat gains (specific annual heat demand, internal and solar heat
gains)
Heat loss form factor (compactness)
Pros Intuitive, transparent, accurate
Integrated to Google SketchUp V8 (free)
Quick result generation
Reasonable license option
Exportable to PHPP
Result consistency
Cons Redrawing of windows
SketchUp components excluded from energy analysis
Unable to input a climate file
Unable to save user-defined settings
WWR missing
Manual assigning of TFA often necessary
Obstructing objects and thermal bridges can be added to the
model but shading effects are only considered in PHPP
Simulation
assumptions
Default airflow, heat recovery efficiency and design temperature
(modifiable in PHPP)
Running time Within seconds
Documentation designPH user manual
Remarks Window frame width is associated with window type
Presumed overlapping between area groups TFA and floor slab /
basement ceiling
Design alternatives of three typical residential buildings
In the test on Stockholmshus case, four tools generated satisfying results: EE, EcoDesigner,
Sefaira and designPH. All Revit energy analysis applications computed extremely high
energy uses and GBS optimization did not succeed in reducing it to an acceptable level. In
fact, the spreadsheet for GBS default settings contains more than 1000 rows and most of
them are not open for editing. The underlying model assumptions might have a significant
impact on final energy outcome and lead to unrealistic results.
53 | Test
Further, the IFC model corresponds to a late design stage and such detailing level is rarely
available in the conceptual phase. The stagnancy of AEC industry being a well-known
subject, the deployment of BIM has made uneven progress throughout the business. Due
to the lack of high-quality data in early stage, the tools need to be tested with simple
volumes or even loose geometries.
As architects work primarily in CAD environment, three typical residential buildings have
been modelled in both ArchiCAD and SketchUp. Lamellhus refers to a building with a high
ratio between length and width; punkthus with a square-like footprint; and vinkelhus,
literally translated by “angle house”, is characterized by two wings forming a right angle.
ArchiCAD
Lamellhus, length 20m, width 10m
Punkthus, length 15m, width 15m
Vinkelhus, wing length 16m, wing width 8m
ArchiCAD has a relatively rigid tool architecture that makes design modifications extremely
delicate. In fact, to add a story in ArchiCAD requires successively:
Add a top floor
Move the roof to the top floor
Create a top floor slab
Attach external walls to the top floor
Add windows to the top story
Create a new zone
Test | 54
Add the new zone to thermal block
Assign thermal properties for the new floor slab and windows
Update Energy Model Review, Update Zones
Start Energy Simulation
Considering the process complexity, no model changes have been performed in ArchiCAD.
SketchUp
Simple, flexible, SketchUp has attracted attention from architects to engineers for its high
usability. SketchUp can further make each story a component so that design modifications
become even easier.
Sefaira
Sefaira can perform energy analysis on story components but is unable to apply story-
specific construction sets. Sefaira Architecture recalculates energy use based on building
volume changes.
Lamellhus, length 20m, width 10m
Punkthus, length 15m, width 15m
Vinkelhus, wing length 16m, wing width 8m
Once uploaded to Sefaira Systems, following inputs have been refined:
Automated blinds and shades with solar gain threshold 300 W/m2
55 | Test
Equipment and lighting power densities respectively 1 W/m2 and 1.5 W/m2
Outside air information: 10.5 L/s/person, 0.35 L/m2/s, 0.5 ACH
Design temperatures 20°C for heating and 25°C for cooling
Operation schedule 24/7
Zoning strategy: one zone per floor
Sefaira Systems then overrides WWR and orientation to create alternatives with different
percentage glazing or project north.
designPH
All windows in designPH need to be drawn with a predefined dynamic component to be
correctly computed by designPH. Window can be inserted manually or converted from
rectangular shapes. Its properties (opening width and height, frame and glazing type) can
be edited under Component Options. Users can define their own frames and glazing under
components and apply them to the model. Three typical residential building models
rendered by area group are shown below.
Lamellhus, length 20m, width 10m
Punkthus, length 15m, width 15m
Vinkelhus, wing length 16m, wing width 8m
Except for predefined windows, designPH is unable to consider SketchUp components
which makes modifications more difficult. To get around this, users can explode a copy of
the original model for calculation purpose.
Evaluation | 56
Evaluation
Delphi Method
Delphi method is widely used in multi-criteria decision analysis to minimize bias. The
method consists in two or more rounds of questionnaires. After each round, an aggregate
is produced based on individual ranked list of criteria and communicated to all participants.
Participants are encouraged to reconsider Delphi method values equally the expertise of
each stakeholder and prevents distortion from peer pressure.
To properly evaluate the overall quality of BES tools, a reference group composed of city
planners, energy experts and KTH has concluded individual weights for each assessment
criterion proposed in §3.3. The weights represent criteria’s relative importance in early-
stage of building design and a total of 40 was allocated. However, the final ranking is only
valid within the project scope and should not be generalized.
Decision matrix
In §5.1, all tools tested on Stockholmshus case were provided with descriptive tables about
theirs inputs, outputs and pros and cons. An individual score for each tool-criterion
combination can be deduced from them. The scores range from -2 to 2, -2 corresponds to
the worst case, 2 to the best and 0 if information is missing. The scores are multiplied by
corresponding criteria weights and added up to establish an overall relevance. As
mentioned in §6.1, the scores highly depend on stakeholders and are only meaningful under
the specific context.
57 | Results
Results
Stockholmshus case
Table 11 shows the energy uses computed by eight selected programs in Stockholmshus test.
Due to calculation method and underlying assumptions, the results vary greatly from one
another.
Table 11 Stockholmshus test results, unit: kWh/m2/year
Program Output
category Result Simulation assumptions
EA
EUI 288 Revit Energy Settings
EUI 153
Best scenario in GBS
Building orientation +180°
Southern WWR 0.3
Roof construction R60
Lighting power density 100% less than base
run
Insight EUI 177 Revit Energy Settings and Insight defaults
GBS EUI 326
GBS project defaults
Assumes blank surfaces for solar PV
analysis
ASHRAE 90.1 High efficiency heat pump
EE Heating
demand
26
Surface heat transfer (cf. §10.1)
Human heat gain 80 W/person
Operating hours 07-17
Heat recovery enabled
One zone per floor
One thermal block for the whole building
EcoDesigner Heating
demand 43
Simulation assumptions in EE
Heat recovery efficiency 80%
Sefaira
EUI 41 Sefaira Architecture for Revit
EUI 38 Sefaira Architecture for SketchUp
Model simplification
EUI 51.5
Sefaira Systems (upload from SketchUp)
Infiltration rate 1.9 m3/m2h
Operating hours 07-17
OpenStudio / One thermal zone per floor
Rooms of the same story merged
designPH
Heat
demand 12 Model simplification
Heat
demand 19 Rooms of the same story merged
Results | 58
Three typical building volumes
EcoDesigner
Table 12 shows energy outcomes and model characteristics for three typical residential
buildings in ArchiCAD.
Table 12 ArchiCAD results, unit: kWh/m2/year
Models Lamellhus (200 m2) Punkthus (225 m2) Vinkelhus (192 m2)
Charac. Heating Charac. Heating Charac. Heating
Original N-S1 38.7 N-S 33.6 N-S 43
3 stories 3 stories 3 stories
FF2 1.22 FF 1.11 FF 1.34
WWR 0.18 WWR 0.16 WWR 0.18 1: North-South, building orientation 2: Form Factor, the ratio between envelope area and floor area
Sefaira
Table 13 and 14shows heating energy in Sefaira for three typical residential buildings and
their alternative designs.
Table 13 Sefaira Systems results, unit: kWh/m2/year
Models Lamellhus (200 m2) Punkthus (225 m2) Vinkelhus (192 m2)
Charac. Heating Charac. Heating Charac. Heating
Uploaded
and
refined
N-S 55 N-S 53 N-S 58
3 stories 3 stories 3 stories
FF2 1.23 FF 1.13 FF 1.33
WWR 0.24 WWR 0.22 WWR 0.24
Orientated E-W3 55 E-W 53 E-W 58
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.24 WWR 0.22 WWR 0.24
Higher
percentage
glazing
N-S 56 N-S 53 N-S 60
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.4 WWR 0.3 WWR 0.4
Lower
percentage
glazing
N-S 60 N-S 55 N-S 62
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.1 WWR 0.15 WWR 0.1 3: East-West, building orientation
59 | Results
Table 14 Sefaira Architecture results, unit: kWh/m2/year
Models Lamellhus (200 m2) Punkthus (225 m2) Vinkelhus (192 m2)
Charac. Heating Chara. Heating Charac. Heating
Original
N-S
26
N-S
24
N-S
29 3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.26 WWR 0.23 WWR 0.25
Add a
story
N-S
24
N-S
22
N-S
27 4 stories 4 stories 4 stories
FF 1.15 FF 1.05 FF 1.25
WWR 0.26 WWR 0.24 WWR 0.25
Different
form
factor
N-S
25
N-S
23
N-S
28 3 stories 3 stories 3 stories
FF 1.2 FF 1.08 FF = 1.31
WWR 0.26 WWR 0.24 WWR 0.25
designPH
Table 15 shows heating demand in designPH for three typical residential buildings and
their alternative designs.
Table 15 designPH results, unit: kWh/m2/year
Model Lamellhus (200 m2) Punkthus (225 m2) Vinkelhus (192 m2)
Charac. Heating Charac. Heati
ng
Charac. Heati
ng
Original N-S 20.3 N-S 17.4 N-S 21.9
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.26 WWR 0.23 WWR 0.25
Orientated E-W 21.7 E-W 18.1 E-W 23.2
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.26 WWR 0.23 WWR 0.25
Add a story N-S 19.2 N-S 16.3 N-S 20.6
4 stories 4 stories 4 stories
FF 1.15 FF 1.05 FF 1.25
WWR 0.26 WWR 0.24 WWR 0.25
Different
form factor
N-S 19.6 N-S 16.4 N-S 21.6
3 stories 3 stories 3 stories
FF 1.2 FF 1.08 FF 1.31
WWR 0.26 WWR 0.24 WWR 0.25
Different
percentage
glazing
N-S 19.5 N-S 17 N-S 21.5
3 stories 3 stories 3 stories
FF 1.23 FF 1.13 FF 1.33
WWR 0.14 WWR 0.13 WWR 0.14
Results | 60
Multi-criteria decision analysis
The reference group proposed following weighting system (see Table 16) for assessment
criteria to represent their priorities in early-stage of building design. The final decision
matrix is shown in Table 17.
Table 16 Weighting system for proposes assessment criteria
Weight
Simplicity (S) 7
Prerequisite (B) 6
Input options (I) 5
Reliability (Q) 5
License cost (C) 5
Program
adaptability (S)
4
Output categories
(O)
3
Usability (U) 3
Result
presentation (P)
2
Table 17 Decision matrix of eight CAD program-integrated BES tools
Tools B I O P Q S E A C Total
Weight 6 5 3 2 5 7 3 4 5
EA 1 1 1 2 -1 1 2 2 0 34
GBS 1 1 1 1 -1 1 2 2 0 32
Insight 1 1 1 1 -1 2 1 2 0 36
EE 1 2 -1 2 1 1 2 2 0 43
EcoDesigner 1 2 2 2 1 1 2 1 0 48
Sefaira 1 1 1 1 0 1 1 2 1 39
OpenStudio -2 1 1 2 -1 -1 2 2 2 12
designPH 1 0 1 0 2 2 1 1 1 45
The four highest ranked tools (EcoDesigner, EE, designPH and Sefaira) are also the only
programs that generated realistic energy results for Stockholmshus case.
61 | Limitations
Limitations
The multi-criteria decision analysis showed that none of the tested BES tools has the
optimal performance with respect to all criteria architects prioritize in the conceptual phase.
Regarding inherent architecture, BES tools are penalized by underlying simulation
assumptions and context-specific terminology. Concerning model robustness, many suffer
from result inconsistency and program instability which affects greatly the scientific
validity. From a theoretical perspective, low predictive value and lack of high-quality data
undermine model generalizable properties. In addition, few software provide adequate user
support which decrease software usability. For the Stockholmshus test, simplified models
need to be further validated against the original one.
The current chapter discusses the limitations of early-stage suitable BES tools and proposes
six reasons for their imperfect functionalities.
Underlying simulation assumptions
Energy simulation requires a large number of input parameters but BES tools masked most
of them for the sake of clarity. They opened limited options for customization and apply
default values elsewhere. Other underlying assumptions include calculation method
related to the specific energy approach under development context, such as consideration
of tenant electricity in internal heat gain.
In addition, one program might propose various applications for different audiences
(architects, energy analysts, building system engineers, real estate managers, etc.) that
often differ in detailing level and simulation assumptions. As results, platform conversions
within one program are also subject to deviations. Concrete examples include import from
Sefaira Architecture to Sefaira Systems and update from Energy Evaluation to EcoDesigner
(see Table 11).
Ambiguous terminology
If the program is willing to compromise customizations for clarity and usability, it has often
failed to provide an exact definition of the technical terms it refers to. As building
terminology changes from one continent to another, specifications are indispensable to
understand the simulation approach of each program.
Legislative context
Each program was developed aiming at a particular market (energy code, building
certification system, etc.). As they comply with region-specific standards or requirements,
different platforms are not always interchangeable between them and deviations of all
scales have been observed in the past.
Even limited to Nordic countries tools, the problem persists with the continuous update of
building regulations. Due to the necessary R&D time in software companies, the tools are
inevitably a step behind specification amendments. The problem is highlighted with FTX
system. Among all the tools, only EcoDesigner offers the possibility to input heat recovery
efficiency for commercial ventilation and most of the tools integrate HVAC systems
according to ASHRAE 90.1 or even older versions.
Limitations | 62
Energy approach
Most of the currently available BES tools use either EnergyPlus or DOE-2 as simulation
engine. Based on thermodynamics principles, these engines rely on heat balance for energy
calculations. In other words, direct inputs in these programs involve solely fundamental
physical quantities such as volume, heat capacity, thermal conductivity, density, mass,
pressure, temperature, etc.
However, such detailed information is not always accessible to users without deep
understanding of building engineering so that predefined aggregated system is imperative
in architect-oriented simulation tools. In particular, a FTX system can be constructed
manually in Revit MEP but such work is excessively complicated in early design stage.
Insufficient level of documentation
A handful of tools provide well-explained and clearly-constructed written manual and most
of them rely on training videos, online user guide or even community forum. If simulation
steps can be reproduced as in the tutorial, underlying assumptions and technical
terminology are poorly documented. Another problem consists in outdated information.
Revit online guide for Energy Analysis cites that when Export Category is set to Rooms,
user can choose to Include Thermal Properties. The feature is however invisible nowadays
and leads to confusions affecting Insight use. Another example concerns SketchUp model
view in Google Earth which is no longer available after Trimble has purchased the software.
In absence of adequate support, peer-to-peer problem solving is often required.
Model validation
To perform energy analysis, all models used in the Stockholmshus test have undergone
different degrees of simplifications (substitution of 3D components by 2D planes, merging
of thermal zones, etc.).
Sefaira Architecture plug-in for Revit shows an energy use intensity of 41 kWh/m2/year for
the IFC-converted model while the same plug-in for SketchUp shows an EUI of 44
kWh/m2/year for the manually rebuilt model. Input parameters being the same, the
difference falls within the confidence interval of 10%. Therefore, the simplified model can
be considered as a good representation of the original one.
Further, a simplified model with merged rooms from the same level is proposed in
designPH to facilitate the assigning of treated floor area. While removing internal walls,
floor area increases and annual heat demand goes up from 11.7 to 18.8 kWh/m2/year. The
difference being smaller than the safety gap (10 kWh/m2/year), the “one thermal zone per
floor” approach kept for energy simulation in the early-stage where space division is rarely
available.
63 | Conclusion
Conclusion
The project was conducted in a relatively short period of time and despite the best effort
made, findings are inevitably incomplete and subject to various limitations in terms of
resource (license, training, budget, etc.).
The literature study suggested CAD program-integrated tools as ideal solutions for early-
stage energy simulation purpose. However, the Stockholmshus case proved them to be less
optimistic on a real case. In fact, their description in §3.2.3 are purely based on
demonstrational tests following user guide. As real cases are usually more complex, careful
manipulations are required to obtain good software performance. Insufficient and outdated
documentation has thus decreased program usability and Autodesk energy applications
and OpenStudio plug-in are eliminated due to poor simulation capabilities.
The remaining programs are then tested on simple building models to propose design
alternatives varying orientation, volume and glazing percentage (except for ArchiCAD add-
ons where changes are difficult to perform). As for results, Sefaira has a significant gap
between SketchUp plug-in and online application but both interfaces contain deliberately
limited input options. Sefaira further breaks down the energy consumption into end-uses
but fails to specify the underlying calculation methods.
While Sefaira employs typical American technical (energy use intensity), designPH
provides result categories in commonly accepted European terminology (specific heat
demand, heat loss form factor, etc.). However, designPH does not allow customization of
ventilation airflow nor heat recovery efficiency and Passive House defaults values are
different from those used for Stockholmshus.
In conclusion, all programs suffer from different degrees of incompatibility and
complications and their energy results are not as reliable as one might believe. In fact, each
program has its own energy approach and simulation assumptions and results might vary
greatly from one platform to another. Within one application, the impact of design
alternatives can be approximately reflected by result variations but the number itself
cannot be used as reference to building energy performance in operation nor even to the
late stage with complete and data and building systems.
The imperfect functionalities of early-stage suitable BES tools have opened possibilities for
future optimizations.
Future perspectives | 64
Future perspectives
Model calibration
As mentioned in §2.3, energy models need to be manually calibrated to reduce the gap
between prediction and observation. In absence of building operation data, this process is
solely based on past experiences. In fact, most of the BES tools propose input options at
two levels: basic and advanced and the distinction is less justified by relevance of energy
features than accessibility to users. Therefore, any option could have a non-negligible
impact on final energy use.
However, users do not always have the time to explore every inputs and some information
might be difficult or even impossible to obtain in early-stage. To generate realistic energy
results, preliminary tests need to be performed to determine an appropriate set of
background variables that have relatively significant impact on energy use. A concrete
example is Surface Heat Transfer under simulation options of Energy Model Review in
Energy Evaluation, ArchiCAD. The terms designate heat transfer coefficients in dynamic
energy balance simulation. While Energy Evaluation online guide recommends to keep
default values, they prove to be critical in energy simulation and have thus been calibrated
to empirically found factors during all tests (internal convective 7.69 W/m2K and external
combined 25 W/m2K).
Due to program-specific terminology and simulation approach, model calibration needs to
be performed for every new BES tool and even for every new model if necessary. The time-
consuming process is believed to be much easier with help from software developers.
District level modelling
In city planning, building energy simulation should not be performed on an isolate thermal
mass but on the aggregate consisting of buildings, surroundings, and interactions between
them. In the literature, district level energy modelling has been tackled by means of
software coupling which enables information exchange between computation codes.
Li et al. [66] proposed an energy model integrated with geographical information system
to simulate mutual shading. Bouyer et al. [67] compared mineralized and vegetated design
scenarios to assess the impact of microclimate on building energy performance (see Fig.59).
As BES tools define theoretically building outer boundary conditions, interactions with its
surroundings are generally ignored. To study building energy performance in different
urban configurations, the authors then coupled CFD with thermo-radiative simulation
tools. Similarly, Yi & Malkawi [68] integrated CFD with Energy Simulation (ES) to analyze
buildings at district level.
65 | Future perspectives
Fig 59 Two urban configurations, source: [18]
Software reprogram
If underlying simulation assumption contradicts with reality, a feasible solution is to
reprogram the software to incorporate context-specific values. As statistical calculation
models do not reproduce the physical processes within the building but rely on empirically
found correlation between factors, the reprogram can either embed these values in the new
assumption or open them for editing. Being the last resort, software reprogram can produce
satisfying outcomes but will increase drastically R&D costs.
References | 66
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Workflow of Revit energy analysis applications | 70
Workflow of Revit energy analysis applications
The workflow for creating an energy model in Revit includes step by step:
Generate 3D view
Open Energy Settings under Energy Analysis tab
Set Location
Change Analytical Mode to Use Conceptual Masses and Building Elements
Refine Project Phase, Analytical Resolutions if necessary
Open Advanced Options
Modify Target Percentage Glazing if necessary
Choose adequate Building Type, Operating Schedule and HVAC System, Export
Category
Edit Outdoor Air Information
71 | Workflow of Revit energy analysis applications
Override Schematic Types. In fact, Revit incorporates three detailing levels for
construction types. Conceptual Types contain general information about building
enclosure (lightweight vs heavyweight, insulation degree); Schematic Types provide
specific construction sets; and Detailed Elements use thermal properties associated
with material layers.
Create Energy Model under Energy Analysis
Energy Analysis and Insight workflows are slightly different after the energy model has
been created. They will be separately described in the following sections.
Energy Analysis
Energy Analysis continues with previously created energy model:
Run Energy Simulation under Energy Analysis, if Create a new project is selected,
Revit Energy Settings will apply; if Use an existing project is selected, GBS project-
specific settings will apply.
Open Results & Compare under Energy Analysis
Export Energy Analysis report to PDF format
Workflow of Revit energy analysis applications | 72
Insight 360
Insight continues with previously created energy model:
Generate Insight under Insight tab
Click Insight
Flip EUI to see ECR
Flip energy factor widgets to see their influence line charts with respect to energy
performance
Create customized design alternative combing energy factors
Visualize heating and cooling loads
Visualize PV panels
Green Building Studio (.gbXML)
All energy models in Energy Analysis and Insight use Green Building Studio projects to run.
Furthermore, Energy Analysis can further choose to run simulation on an existing model
using GBS customized settings which can be created following the steps below:
Access Green Building Studio online service
Create a New Project
Define Project Name, Building Type, Schedule
Set Project Location
Go to Project Defaults
73 | Workflow of Revit energy analysis applications
Spaces properties (space type, lighting/equipment power density, area per person,
design temperature)
Zones properties (setpoint temperatures, outside air per person)
Surfaces constructions (pitch roof, exterior wall, interior floor, slab on grade, door)
Openings type
HVAC equipment
Save changes
Upload gbXML file to the project or select user-defined GBS project as template when
running energy simulation in Revit
Click Base Run to see simulation results
Create customized alternative under Design Alternatives
Workflow of ArchiCAD energy add-ons | 74
Workflow of ArchiCAD energy add-ons
Similar to Revit, ArchiCAD has a high detailing level and is mainly used from schematic to
late design stage. Its workflow for creating an energy model is described as follows:
Select Zone tool
Define Name, Number, Top/base constraints in Zone Default Settings
If Construction Method is set to Manual, zone limits need to be drawn in the
corresponding floor plan; otherwise ArchiCAD identifies automatically space
boundaries but later offers the possibility to merge or split zones
Click delimited area to apply zone properties
Repeat above steps until all zones have been created
Check Zone in View > Elements in 3D View > Filter and Cut Elements in 3D
Activate 3D view
Connect the upper zone to the roof if necessary
As an integrated plug-in to ArchiCAD, Energy Evaluation then enables the refining of
energy model.
Energy Evaluation
Open Energy Model Review dialog box
Add new thermal block (Name, Operation Profile)
75 | Workflow of ArchiCAD energy add-ons
Add zones to selected thermal block
Add building systems to selected thermal block
Update Energy Model Review, Update Zones until Structures and Openings appear
Under Structure tab, define U-values and infiltration for External/Internal Structures.
ArchiCAD further allows Showing Active Element in 3D View and structure grouping
to facilitate property editing. Same logic also applies to Openings.
Under Openings tab, define U-values, infiltration and solar transmissions for
Doors/Windows
Workflow of ArchiCAD energy add-ons | 76
Specify Climate Data
Refine Environment Settings (Surface Heat Transfer, Soil Type, Horizontal Shadings)
Customize Operation Profiles (Human Heat Gain, Hot Water Consumption,
Operating Schedule, Indoor Temperatures, Occupant Density, Lighting/Equipment
Power Density)
Customize Building Systems
Update Energy Model Review, Update Zones
Start Energy Simulation
77 | Workflow of ArchiCAD energy add-ons
EcoDesigner
EcoDesigner can be obtained by reserving its license in energy simulation options and
restarting the program. The energy modelling dialogue then opens in advanced mode.
Central Heating
Solar Thermal Collector if selected as On-site Equipment
Time Schedule for Mechanical Ventilation (Operation Schedule, Heat Recovery
Operating Parameters)
Workflow of SketchUp energy plug-ins | 78
Workflow of SketchUp energy plug-ins
Build a conceptual model with reproduced positions and surface dimensions of building
parts
Delete curtain walls
Sefaira Systems
Sefaira Architecture plug-in for SketchUp verifies that the model is correctly analyzed,
defines thermal properties for building enclosure, and uploads the model to Sefaira
Systems for a more detailed analysis.
Open Sefaira plug-in
Set Building Type and Site Address (cities only)
Under Entity Palette, click Show Entity Types to check surface tags, if not correctly
identified, manual assigning is required
Under Model Properties, Refine U-values, SHGC, Infiltration Rate, Ventilation Rate,
Lighting/Equipment Power Density
79 | Workflow of SketchUp energy plug-ins
Click Upload to Sefaira then Continue to Sefaira
Select Create New Web App Project
Define Project Name and Create New Project
Choose HVAC System Type
Refine Envelope, change to Residential, override WWR and orientation if needed
Add Shading
Customize Space Use (Occupant density, Equipment/Lighting Power Density, Outside
Air Information, Setpoint Temperatures, Daily and Weekly Operating Schedule).
Sefaira can further save user-defined settings.
Workflow of SketchUp energy plug-ins | 80
Add PV
Define Zoning strategy
Use Update to run design alternatives
OpenStudio
The plug-in extrudes floor plans only with OpenStudio tools which generates additional
work to reconstruct the model. Once spaces created, they are refined with type,
construction set and parent thermal zone. The model is then exported to OpenStudio
Application for simulation.
Rebuild OpenStudio model with dedicated tool Create Space from Diagrams
Set Attributes to Spaces (Type, Construction Set and Thermal Zone). Space properties
can be later modified in OpenStudio Application.
Open OpenStudio Application
Upload Weather File, Design Day File
81 | Workflow of SketchUp energy plug-ins
Create customized construction types with U-values (Materials > Constructions >
Construction Sets)
Create space schedules
Create zone equipment
designPH
TFA default estimation in designPH is based on WARM (Low Energy Building Practice)
and coefficients of 100%, 60% and 50% are respectively employed for standard areas,
corridors and low ceiling areas. As designPH separates TFA from ground slab and building
footprint, manual refining is often necessary.
Draw designPH-recognizable windows with Convert Face to Window tool
Launch designPH
Create customized Assemblies
Create customized Components (Glazing, Frames)
Update window options
Workflow of SketchUp energy plug-ins | 82
Assign Area Group
Assign U-value
Render by Components, different colors indicating different U-values
Render by Area Group and Run Analysis
83 | Annex A: Energy Analysis report for Stockholmshus
Annex A: Energy Analysis report for Stockholmshus
Annex B: Energy Evaluation report for Stockholmshus | 84
Annex B: Energy Evaluation report for Stockholmshus
85 | Annex C: EcoDesigner report for Stockholmshus
Annex C: EcoDesigner report for Stockholmshus
Annex D: Comparative table of BES tools | 86
Annex D: Comparative table of BES tools Table 18 summarizes the assessment of 35 tools described in §3.2.3 with respect to above criteria. Red color indicates that the corresponding ingredient does not meet with the requirement.
Table 18 Table of comparison of BES tools
Tools Simulation overview Calculation quality
Usability Availability Cost Prerequisite Inputs Outputs Presentation Reliability Complexity
DOE-2
Good knowledge
on
thermodynamic
concepts
Climate file
Heating system
Orientation
Geometry
U-value
Airflow
Heat losses and gains
Heating and cooling demand
Fuel demand
Cost
Renewables
Regulatory compliance
Text files High High All stages All world Free
EnergyPlus
Good knowledge
on
thermodynamic
concepts
Climate file
Heating system
Orientation
Geometry
U-value
Airflow
Energy consumption
Renewables
Regulatory compliance
Text files High High All stages All world Free
RIUSKA
Geographic location
Heating system
Orientation
Geometry import via IFC
U-value
Airflow
Occupant comfort
Energy consumption
Renewables
Regulatory compliance
Text files Medium Medium to high
eQUEST
Good knowledge
on building
technology
Geographic location
Heating system
Orientation
Geometry (possible DWG import)
U-value
Airflow
Electricity consumption
Gas consumption
Renewables
ASHRAE 90.1 compliance
Graphs Medium to high High to medium Early conceptual
stage All world Free
BDA Basic skill in
CAD drawings
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Temperature
Airflow
Lighting electricity
Daylight illuminance
Cost
Energy consumption
Renewables
Regulatory compliance
Graphs Medium to low Medium to low Schematic to
detailed stage US or Canada Free
DesignBuilder
Good knowledge
on building
energy
simulation
Geographic location
Heating system
Orientation
Geometry (possible export from
Revit)
U-value
Airflow
Temperature
Heat balance
Indoor comfort
Airflow
Internal gains
Renewables
UK energy code compliance
Graphs Medium Medium to low All stages All world
899 EUR for
Architectural
Essentials
Simergy
Basic knowledge
on building
design
Geographic location
Heating system
Orientation
Geometry import from BIM
U-value
Airflow
Heating and cooling hours
Site energy intensity
Electricity consumption
Renewables
Title 24 compliance
Graphs Medium Medium Early stage US only 1125 USD
87 | Annex D: Comparative table of BES tools
DPV Basic skills in
Revit
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Energy losses and gains
Heating and cooling energy
Renewables
Regulatory compliance
Graphs Medium Medium Early stage Only for Revit
2014 Free
ZEBO
Basic knowledge
on building
energy
simulation
Geographic location
Heating system
Cardinal orientations only
Rectangular forms only
U-value
Airflow
Energy consumption
Psychometric
Sensitivity analysis
Renewables
Regulatory compliance
Graphs Medium Medium to high Detailed stage Hot climates
BSim
Good knowledge
of building
energy
simulation
Geographic location / climate file
Heating system
Orientation
Geometry import from DXF files
U-value
Airflow
Indoor climate
Thermal and moisture conditions
Daylight
Renewables
Danish building regulations
compliance
Graphs Medium Medium Conceptual stage Mainly Denmark
SBi 32000 DKK
BV2-arch Basic skill in
CAD drawing
Location locked by client
Heating system
Orientation
2D drawing and 3D viewing
U-value
Airflow
Heating and cooling demand
Renewables
Regulatory compliance
Graphs Low Low Early stage
Mainly Sweden
CIT Energy
Management
16000 SEK
IDA ICE
Experiences with
building energy
simulation
Geographic location
Heating system
Orientation
Geometry import from BIM/CAD
U-value
Airflow
Airflow
Total heating and cooling
Daylight
Delivered energy
Renewables
ASHRAE 90.1 compliance extension
Graphs and
reports Medium to high Medium All stages
Mainly Sweden,
available for
Norway and
Denmark
18000 SEK
IDA ESBO
Experiences with
building energy
simulation
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Heating and cooling loads
Energy consumption
Renewables
Regulatory compliance
Reports Medium Medium to low Early stage
Mainly Sweden,
available for
Norway and
Denmark
VIP-Energy
Good knowledge
on building
energy
simulation
Climate data
Heating system
Orientation
Geometry from building parts,
visualization unavailable
U-value
Airflow
Energy balance
Cost
Renewables
Regulatory compliance
Tables and
graphs Medium Medium All stages All world 28000 SEK
EHK
Good knowledge
on building
technology
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Heat losses
Energy consumption
Delivered energy
Renewables
Regulatory compliance
Calculation sheet Low Medium Schematic stage Sweden a priori 6000 SEK
Annex D: Comparative table of BES tools | 88
Derob-LTH
Good knowledge
on building
technology
Climate data
Heating system
Orientation
Geometry by coordinates,
visualization unavailable
U-value
Airflow
Thermal comfort
Visual comfort
Energy consumption
Renewables
Regulatory compliance
Graphs Medium to low Medium Schematic stage All world 1200 EUR
HAM-Tools
Deep
understanding of
fluid mechanics
and heat transfer
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
HAM balance
Heating and cooling demand
Renewables
Regulatory compliance
Graphs High High Detailed stage Free
Energy10
Basic knowledge
on building
energy
simulation
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Energy demand
Heat supply
Electricity demand
Renewables
Danish building code compliance
Tables Low Medium Detailed stage Denmark a
priori
Ecotect
Good knowledge
on Revit
modelling
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Sun and shadow
Daylighting and lighting
Thermal performance
Whole building energy analysis
Renewables
Regulatory compliance
Graphs and
renderings Medium to high Medium to high All stages
No longer
available /
Vasari
Good knowledge
on Revit
modelling
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Wind analysis
Climate analysis
Daylighting and electric lighting
analysis
Whole building energy analysis
Renewables
Regulatory compliance
Graphs Medium to high Medium to high All stages No longer
available /
Energy
Analysis for
Revit
Good knowledge
of Revit
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Carbon emissions
Energy use
Heating and cooling loads
Renewables
Regulatory compliance
Summary
reports Medium to low Low to medium All stages All world
Included in
Autodesk 360
GBS
Good knowledge
of Revit
including
gbXML export
feature
Geographic location
Heating system
Orientation
Geometry import from gbXML,
visualization unavailable
Implicit U-value
Airflow
Energy consumption
Energy cost
Carbon emissions
Renewables
Regulatory compliance
Pie charts and
reports Medium to low Low to medium All stages All world
Included in
Autodesk 360
Insight Basic skill in 3D
drawing
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Energy use intensity
Energy cost
Energy factor analysis
Renewables
Benchmark comparison (Net Zero
Standard, Architecture 2030
Challenge)
Graphs Medium to low Low Early stage All world Included in
Autodesk 360
89 | Annex D: Comparative table of BES tools
EE Good knowledge
of ArchiCAD
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Energy consumption
Energy balance
Energy cost
Carbon emissions
Renewables
Regulatory compliance
Report Medium to high Low to medium All stages From Strusofts
klimatserver
Included in
ArchiCAD
EcoDesigner Good knowledge
of ArchiCAD
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Energy consumption
Energy balance
Energy cost
Carbon emissions
Renewables
Regulatory compliance
Report Medium to high Low to medium All stages
AU, BR, CA, DK,
EE, FI, HU, LT,
NL, SI, ZA, SE,
UK
Additional
purchase in
ArchiCAD
Sefaira
Basic skills in
Revit or
SketchUp
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Energy use intensity
Energy segments
Daylighting
Renewables
Regulatory compliance
Graphs Medium to low Low to medium Early to schematic
stage All world 907 EUR/year
IES VE
Basic skills in
SketchUp (or
Revit)
Geographic location
Heating system (Revit only)
Orientation
Geometry
U-value
Airflow
Daylight analysis
Solar analysis
Whole building energy use
Heating and cooling loads
Renewables
Regulatory compliance
Tables and
graphs Medium Medium Conceptual stage All world
5200
USD/year for
architectural
package
OpenStudio
Good knowledge
of building
technology or
software
development
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Energy use
Energy cost
Renewables
Regulatory compliance
Reports and
graphs Medium to low Medium All stages
EnergyPlus
weather file Free
designPH Basic skills in
SketchUp
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Annual heating demand
Solar heat gain
Renewables
Regulatory compliance
Tables High Low Early stage Primarily
Europe
300 EUR for
PHPP users
Grasshopper
and Ladybug
Tools
Good knowledge
of Rhino and
parametric
design
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Annual heating demand
Renewables
Regulatory compliance
Text files High High All stages All world 995 EUR for
Rhino
ESP-r
Understanding
of thermo-
physical
processes in the
buildings,
environmental
systems and
controls
Climate file
Heating system
Orientation
Geometry
U-value
Airflow
Airflow
Electricity
Indoor air quality
Lighting assessments
Renewables
Regulatory compliance
Graphs High High All stages Primarily
Europe Free
Annex D: Comparative table of BES tools | 90
MIT Design
Advisor
Good knowledge
on building
technology
Geographic location
Heating system
Cardinal room orientations
Predefined building shapes
U-value according to ASHRAE
90.1 2001
Airflow
Energy use
Thermal comfort
Daylighting
Life cycle analysis
Renewables
Building code comparison
Graphs Medium Medium to low Early stage
Main cities
around the
world
Free
TAS
Good knowledge
on building
energy
simulation
Climate data
Heating system
Orientation
Geometry
U-value
Airflow
Energy consumption
CO2 emissions
Operating costs
Occupant comfort
Renewables
Compliance with UK Building
Regulations
Graphs High High All stages All world Free
ECOCITIES Basic knowledge
of city planning
Geographic location
Heating system
Orientation
Geometry
U-value
Airflow
Costs
CO2 emissions
Heating demand
Primary energy demand
Share of renewable energy
Compliance with ISO/EN standards
Tables Medium to low Low Conceptual stage Primarily EU 6000 EUR for
installation
iDbuild
Good knowledge
on building
energy
simulation and
programming
Climate data
Heating system
Orientation and geometry limited
to rooms
U-value
Airflow
Energy performance
Daylight factor
Operating temperature
Indoor air quality
Renewables
Regulatory compliance
Graphs Medium High Schematic stage EnergyPlus
weather data Free
www.kth.se