EXAMENSARBETE INOM 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

KTH SKOLAN 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)  Glazing area (detailed)  Heating systems  U-values (opaque/  Glazing type  Heating control transparent)  Shading/blinds strategies  Heat recovery systems  Blind control  Cooling systems  Light/heavy construction  Orientation (adjusted) (mechanical/free)  Air change rate  Air change rate  Cooling control (appraisal) (detailed) strategies  Space usage  Material adjustment in  Ventilation  Glazing area (appraisal) overheating areas strategies  Floor plan depth  Lighting strategy  Fuel type

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).

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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

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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 Ground slab 0.2 W/m2K Wall 0.15 W/m2K Window 0.9 W/m2K U-values Roof 0.1 W/m2K Floor 0.25 W/m2K Door 1 W/m2K Wall/Roof 0.6 L/ m2s Air leakage at 50 Pa Window/Door 0.8 L/ m2s Ground slab 0.1 L/m2s Direct 50% Solar transmittance factor Total 55% Airflow per person 10.5 L/s/person Airflow per area 0.35 L/m2s Ventilation Air changes per hour 0.5 (ACH) Heat recovery efficiency 80% Heating 20°C Temperature setpoints1 Cooling 25°C Equipment 1 W/m2 Tenant electricity 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  Default occupant density (living area per person) assumptions  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

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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  Default occupant density (living area per person) assumptions  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.

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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)

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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.

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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.

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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  Default airflow, heat recovery efficiency and design temperature assumptions (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 Output Program Result Simulation assumptions category EUI 288 Revit Energy Settings Best scenario in GBS  Building orientation +180° EA  Southern WWR 0.3 EUI 153  Roof construction R60  Lighting power density 100% less than base run Insight EUI 177 Revit Energy Settings and Insight defaults GBS project defaults  Assumes blank surfaces for solar PV GBS EUI 326 analysis  ASHRAE 90.1 High efficiency heat pump  Surface heat transfer (cf. §10.1)  Human heat gain 80 W/person Heating 26  Operating hours 07-17 EE demand  Heat recovery enabled  One zone per floor  One thermal block for the whole building Heating  Simulation assumptions in EE EcoDesigner 43 demand  Heat recovery efficiency 80% EUI 41 Sefaira Architecture for Revit Sefaira Architecture for SketchUp EUI 38  Model simplification Sefaira Sefaira Systems (upload from SketchUp) EUI 51.5  Infiltration rate 1.9 m3/m2h  Operating hours 07-17  One thermal zone per floor OpenStudio /  Rooms of the same story merged Heat 12  Model simplification demand designPH Heat 19  Rooms of the same story merged demand 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 N-S 55 N-S 53 N-S 58 and 3 stories 3 stories 3 stories refined 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 N-S 56 N-S 53 N-S 60 percentage 3 stories 3 stories 3 stories glazing FF 1.23 FF 1.13 FF 1.33 WWR 0.4 WWR 0.3 WWR 0.4 Lower N-S 60 N-S 55 N-S 62 percentage 3 stories 3 stories 3 stories glazing 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 Lamellhus (200 m2) Punkthus (225 m2) Vinkelhus (192 m2) Models Charac. Heating Chara. Heating Charac. Heating N-S N-S N-S 3 stories 3 stories 3 stories Original 26 24 29 FF 1.23 FF 1.13 FF 1.33 WWR 0.26 WWR 0.23 WWR 0.25 N-S N-S N-S Add a 4 stories 4 stories 4 stories 24 22 27 story FF 1.15 FF 1.05 FF 1.25 WWR 0.26 WWR 0.24 WWR 0.25 N-S N-S N-S Different 3 stories 3 stories 3 stories form 25 23 28 FF 1.2 FF 1.08 FF = 1.31 factor 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 Charac. Heati ng 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 N-S 19.6 N-S 16.4 N-S 21.6 form factor 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 N-S 19.5 N-S 17 N-S 21.5 percentage 3 stories 3 stories 3 stories glazing 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 4 adaptability (S) Output categories 3 (O) Usability (U) 3 Result 2 presentation (P)

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 Simulation overview Calculation quality Tools Usability Availability Cost Prerequisite Inputs Outputs Presentation Reliability Complexity  Climate file  Heat losses and gains Good knowledge  Heating system  Heating and cooling demand on  Orientation  Fuel demand DOE-2 Text files High High All stages All world Free thermodynamic  Geometry  Cost concepts  U-value  Renewables  Airflow  Regulatory compliance  Climate file Good knowledge  Heating system  Energy consumption on  Orientation EnergyPlus  Renewables Text files High High All stages All world Free thermodynamic  Geometry  Regulatory compliance concepts  U-value  Airflow  Geographic location  Heating system  Occupant comfort  Orientation  Energy consumption RIUSKA Text files Medium Medium to high  Geometry import via IFC  Renewables  U-value  Regulatory compliance  Airflow  Geographic location  Heating system  Electricity consumption Good knowledge  Orientation  Gas consumption Early conceptual eQUEST on building Graphs Medium to high High to medium All world Free  Geometry (possible DWG import)  Renewables stage technology  U-value  ASHRAE 90.1 compliance  Airflow  Temperature  Geographic location  Airflow  Heating system  Lighting electricity Basic skill in  Orientation  Daylight illuminance Schematic to BDA Graphs Medium to low Medium to low US or Canada Free CAD drawings  Geometry  Cost detailed stage  U-value  Energy consumption  Airflow  Renewables  Regulatory compliance  Geographic location  Temperature  Heating system  Heat balance Good knowledge  Orientation  Indoor comfort 899 EUR for on building DesignBuilder  Geometry (possible export from  Airflow Graphs Medium Medium to low All stages All world Architectural energy Revit)  Internal gains Essentials simulation  U-value  Renewables  Airflow  UK energy code compliance

 Geographic location  Heating and cooling hours  Heating system Basic knowledge  Site energy intensity  Orientation Simergy on building  Electricity consumption Graphs Medium Medium Early stage US only 1125 USD  Geometry import from BIM design  Renewables  U-value  Title 24 compliance  Airflow

87 | Annex D: Comparative table of BES tools

 Geographic location  Heating system  Energy losses and gains Basic skills in  Orientation  Heating and cooling energy Only for Revit DPV Graphs Medium Medium Early stage Free Revit  Geometry  Renewables 2014  U-value  Regulatory compliance  Airflow  Geographic location  Energy consumption Basic knowledge  Heating system  Psychometric on building  Cardinal orientations only ZEBO  Sensitivity analysis Graphs Medium Medium to high Detailed stage Hot climates energy  Rectangular forms only  Renewables simulation  U-value  Regulatory compliance  Airflow  Geographic location / climate file  Indoor climate Good knowledge  Heating system  Thermal and moisture conditions of building  Orientation  Daylight Mainly Denmark BSim Graphs Medium Medium Conceptual stage 32000 DKK energy  Geometry import from DXF files  Renewables  SBi simulation  U-value  Danish building regulations  Airflow compliance  Location locked by client  Heating system  Heating and cooling demand Mainly Sweden Basic skill in  Orientation BV2-arch  Renewables Graphs Low Low Early stage  CIT Energy 16000 SEK CAD drawing  2D drawing and 3D viewing  Regulatory compliance Management  U-value  Airflow  Geographic location  Airflow  Heating system  Total heating and cooling Mainly Sweden, Experiences with  Orientation  Daylight Graphs and available for IDA ICE building energy Medium to high Medium All stages 18000 SEK  Geometry import from BIM/CAD  Delivered energy reports Norway and simulation  U-value  Renewables Denmark  Airflow  ASHRAE 90.1 compliance extension  Geographic location  Heating system  Heating and cooling loads Mainly Sweden, Experiences with  Orientation  Energy consumption available for IDA ESBO building energy Reports Medium Medium to low Early stage  Geometry  Renewables Norway and simulation  U-value  Regulatory compliance Denmark  Airflow  Climate data  Heating system Good knowledge  Energy balance  Orientation on building  Cost Tables and VIP-Energy  Geometry from building parts, Medium Medium All stages All world 28000 SEK energy  Renewables graphs visualization unavailable simulation  Regulatory compliance  U-value  Airflow

 Geographic location  Heat losses  Heating system Good knowledge  Energy consumption  Orientation EHK on building  Delivered energy Calculation sheet Low Medium Schematic stage Sweden a priori 6000 SEK  Geometry technology  Renewables  U-value  Regulatory compliance  Airflow Annex D: Comparative table of BES tools | 88

 Climate data  Heating system  Thermal comfort Good knowledge  Orientation  Visual comfort Derob-LTH on building  Geometry by coordinates,  Energy consumption Graphs Medium to low Medium Schematic stage All world 1200 EUR technology visualization unavailable  Renewables  U-value  Regulatory compliance  Airflow  Climate data Deep  Heating system  HAM balance understanding of  Orientation  Heating and cooling demand HAM-Tools Graphs High High Detailed stage Free fluid mechanics  Geometry  Renewables and heat transfer  U-value  Regulatory compliance  Airflow  Geographic location  Energy demand Basic knowledge  Heating system  Heat supply on building  Orientation Denmark a Energy10  Electricity demand Tables Low Medium Detailed stage energy  Geometry priori  Renewables simulation  U-value  Danish building code compliance  Airflow  Climate data  Sun and shadow  Heating system  Daylighting and lighting Good knowledge  Orientation  Thermal performance Graphs and No longer Ecotect on Revit Medium to high Medium to high All stages /  Geometry  Whole building energy analysis renderings available modelling  U-value  Renewables  Airflow  Regulatory compliance  Wind analysis  Climate data  Climate analysis  Heating system Good knowledge  Daylighting and electric lighting  Orientation No longer Vasari on Revit analysis Graphs Medium to high Medium to high All stages /  Geometry available modelling  Whole building energy analysis  U-value  Renewables  Airflow  Regulatory compliance  Climate data  Carbon emissions  Heating system Energy  Energy use Good knowledge  Orientation Summary Included in Analysis for  Heating and cooling loads Medium to low Low to medium All stages All world of Revit  Geometry reports Autodesk 360 Revit  Renewables  U-value  Regulatory compliance  Airflow  Geographic location Good knowledge  Heating system  Energy consumption of Revit  Orientation  Energy cost Pie charts and Included in GBS including  Geometry import from gbXML,  Carbon emissions Medium to low Low to medium All stages All world reports Autodesk 360 gbXML export visualization unavailable  Renewables feature  Implicit U-value  Regulatory compliance  Airflow

 Energy use intensity  Geographic location  Energy cost  Heating system  Energy factor analysis Basic skill in 3D  Orientation Included in Insight  Renewables Graphs Medium to low Low Early stage All world drawing  Geometry Autodesk 360  Benchmark comparison (Net Zero  U-value Standard, Architecture 2030  Airflow Challenge)

89 | Annex D: Comparative table of BES tools

 Geographic location  Energy consumption  Heating system  Energy balance Good knowledge  Orientation  Energy cost From Strusofts Included in EE Report Medium to high Low to medium All stages of ArchiCAD  Geometry  Carbon emissions klimatserver ArchiCAD  U-value  Renewables  Airflow  Regulatory compliance  Geographic location  Energy consumption  Heating system  Energy balance AU, BR, CA, DK, Additional Good knowledge  Orientation  Energy cost EE, FI, HU, LT, EcoDesigner Report Medium to high Low to medium All stages purchase in of ArchiCAD  Geometry  Carbon emissions NL, SI, ZA, SE, ArchiCAD  U-value  Renewables UK  Airflow  Regulatory compliance  Climate data  Energy use intensity  Heating system Basic skills in  Energy segments  Orientation Early to schematic Sefaira Revit or  Daylighting Graphs Medium to low Low to medium All world 907 EUR/year  Geometry stage SketchUp  Renewables  U-value  Regulatory compliance  Airflow  Geographic location  Daylight analysis  Heating system (Revit only)  Solar analysis 5200 Basic skills in  Orientation  Whole building energy use Tables and USD/year for IES VE SketchUp (or Medium Medium Conceptual stage All world  Geometry  Heating and cooling loads graphs architectural Revit)  U-value  Renewables package  Airflow  Regulatory compliance  Climate data Good knowledge  Heating system  Energy use of building  Orientation  Energy cost Reports and EnergyPlus OpenStudio technology or Medium to low Medium All stages Free  Geometry  Renewables graphs weather file software  U-value  Regulatory compliance development  Airflow  Climate data  Heating system  Annual heating demand Basic skills in  Orientation  Solar heat gain Primarily 300 EUR for designPH Tables High Low Early stage SketchUp  Geometry  Renewables Europe PHPP users  U-value  Regulatory compliance  Airflow  Climate data Good knowledge  Heating system Grasshopper  Annual heating demand of Rhino and  Orientation 995 EUR for and Ladybug  Renewables Text files High High All stages All world parametric  Geometry Rhino Tools  Regulatory compliance design  U-value  Airflow

Understanding of thermo-  Climate file  Airflow physical  Heating system  Electricity processes in the  Orientation  Indoor air quality Primarily ESP-r Graphs High High All stages Free buildings,  Geometry  Lighting assessments Europe environmental  U-value  Renewables systems and  Airflow  Regulatory compliance controls Annex D: Comparative table of BES tools | 90

 Geographic location  Energy use  Heating system  Thermal comfort Good knowledge  Cardinal room orientations Main cities MIT Design  Daylighting on building  Predefined building shapes Graphs Medium Medium to low Early stage around the Free Advisor  Life cycle analysis technology  U-value according to ASHRAE world  Renewables 90.1 2001  Building code comparison  Airflow  Energy consumption  Climate data  CO2 emissions Good knowledge  Heating system  Operating costs on building  Orientation TAS  Occupant comfort Graphs High High All stages All world Free energy  Geometry  Renewables simulation  U-value  Compliance with UK Building  Airflow Regulations  Geographic location  Costs  Heating system  CO2 emissions Basic knowledge  Orientation  Heating demand 6000 EUR for ECOCITIES Tables Medium to low Low Conceptual stage Primarily EU of city planning  Geometry  Primary energy demand installation  U-value  Share of renewable energy  Airflow  Compliance with ISO/EN standards  Climate data  Energy performance Good knowledge  Heating system  Daylight factor on building  Orientation and geometry limited  Operating temperature EnergyPlus iDbuild energy Graphs Medium High Schematic stage Free to rooms  Indoor air quality weather data simulation and  U-value  Renewables programming  Airflow  Regulatory compliance

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