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