Automation in Construction 18 (2009) 153–163

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Automation in Construction

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Building information model based energy/exergy performance assessment in earlydesign stages

Arno Schlueter ⁎, Frank ThesselingInstitute of Building Technologies, Building Systems Group, ETH Zürich, Switzerland

⁎ Corresponding author. Tel.: +41 44 633 3618; fax: +E-mail addresses: schlueter@arch.ethz.ch (A. Schluet

(F. Thesseling).

0926-5805/$ – see front matter © 2008 Elsevier B.V. Aldoi:10.1016/j.autcon.2008.07.003

a b s t r a c t

a r t i c l e i n f o

Article history:

Accepted 12 July 2008

Keywords:

Due to the rising awarenedesigners increasingly havperformance simulation isdecision-making. In order

Building information modelBuilding performanceEnergy analysisExergy analysisDesign supportParametric design

to evaluate the dependencies of performance criteria on form, material andtechnical systems, building performance assessment has to be seamlessly integrated into the design process.In this approach, the capability of building information models to store multi-disciplinary information isutilized to access parameters necessary for performance calculations. In addition to the calculation of energybalances, the concept of exergy is used to evaluate the quality of energy sources, resulting in a higherflexibility of measures to optimize a building design. A prototypical tool integrated into a buildinginformation modelling software is described, enabling instantaneous energy and exergy calculations and thegraphical visualisation of the resulting performance indices.

ss of climate change and resulting building regulations worldwide, buildinge to consider the energy performance of their building designs. Currently,mostly executed after the design stage and thus not integrated into design

© 2008 Elsevier B.V. All rights reserved.

1. Introduction

The operation of buildings accounts for 40% of global CO2

emissions [1]. These emissions are directly linked to the energy abuilding consumes in order to maintain its usability. Heating orcooling energy has to be supplied to maintain a certain comfort level.Additional power is needed to operate lighting, appliances andbuilding service systems.

Due to the increased awareness of energy consumption and relatedCO2 emissions, building regulations such as the European BuildingsDirective [1] in Europe, Minergie in Switzerland [2], or programs suchas LEED [3] in the USA have been established over the last years.Architects and planners are increasingly forced to consider energyconsumption and the environmental impact of their building designs.Building performance is defined differently among professionals andresearchers. In the context of this paper, we define buildingperformance as related to energy consumption, the most importantissue concerning CO2 emissions.

It is widely acclaimed that the most important design decisionsconcerning building sustainability have to be made in the early designstages—that is by the architect or building designer. In commonarchitectural practice however, performance analysis to supportdesign decision-making is only used for the few buildings facingengineering challenges or explicitly focussing on sustainability. The

41 44 633 1047.er), thesseling@arch.ethz.ch

l rights reserved.

lack of integration into the design leads to extensive modificationsafterwards to meet performance criteria.

This practice also leads to buildings that might be sustainableconsidering their energy consumption but not in architectural aspects.

Current developments in computer applications in architecturehave led to impressive results, for example in the fields of advancedgeometry and computer-aided production methods. Both fieldsdirectly address the domain of the architect and are used forprogression in architectural design. Computers are used to enhancethe traditional toolsets. It seems obvious to extend these methods toimplement building performance aspects. However, no tools exist toseamlessly integrate performance assessment into the design processor to support the design and decision-making of the architect orbuilding designer. Holistic performance assessment is not consideredin any kind of computer-aided architectural design (CAAD) environ-ment that architects use.

This is due to several reasons. In the traditional architecturalworkflow, performance assessment is mostly done subsequent to thearchitects design. It is done by the expert, inmost cases the engineer. Alot of expert software exists for every type of simulation of specific andoverall performance of buildings and building components. Availablesimulation tools are therefore aimed at the expert and make explicitexpert knowledge necessary to input the data needed, run thesimulations and interpret the results. In the early design stages, thisdata is often not available. Architects are mostly non-expertsconsidering performance simulation. As generalists, they do notknow about precisely every parameter necessary to run an expertsimulation. But they know about form, materials and preferred

154 A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

technical systems of their building design. This information, if definedduring the design, can be used as input to evaluate buildingperformance. The amount of information and the complexity of itsdependencies makes computational methods necessary [4].

Building performance is measured by using mathematical calcula-tion models. Based on the task, these range from simplified statisticalmodels to specialized physical simulations. To support decision-making, the highest level of precision is not necessary. Performanceassessment for the early design stages has to show the tendencies and,most important, dependencies of decisions.

In our approach we focus on the energy performance of buildings.We expand the common energy analysis by considering the thermo-economic concept of exergy. Exergy analysis takes the quality ofenergy into account. It enables balancing between building form,materials and technical systems and makes a holistic view of thebuilding possible. A building information model is used to storenecessary data and access parameters during the design process.Energy and exergy calculations are directly integrated into thebuilding information modelling editor by a prototypical tool, theDesign Performance Viewer (DPV). The tool enables fast estimation ofenergy and exergy performance of the specific design, facilitatingnecessary parameter input by using non-expert decision criteria.Results are visualized using selected key performance indices andgraphical visualization.

2. Building information modelling

To be able to consider building performance in the early designstages, access to all information defining a building such as its form,materialization and technical systems is necessary. Common, docu-ment-based CAD planning environments do not support thisintegrated view of a building. In machine engineering, the conceptof “semantic datamodels” [5] was established in the 1970s, connectinglogical and physical information. For the needs of the buildingindustry, this concept was adapted for generic “building descriptionsystems” [6], later called “building product models” [7]. Since 2002,the term of “building information models” [8] has been widespread.Building information models enable storing multi-disciplinary infor-mation within one virtual building representation. A buildinginformation models is a “richer repository” [7] than a set of drawings,since it has the ability to store different types of information.

These types of information include geometric, semantic andtopological information. Geometric information directly relates tothe building form in three dimensions. Semantic informationdescribes the properties of components such as u-values of walls.Topological information captures the dependencies of components.Or, as Eastman [7] states, a building information model contains the“form, behaviour and relations of parts and assemblies”.

Building information models have to be distinguished betweenproprietary models established by software companies and open,non-proprietary models such as the Industry Foundation Classes (IFC),developed by the International Alliance for Interoperability (IAI) [9].The IFC serve as an “intelligent, comprehensive and universal datamodel of buildings” [10]. The IFC data model is already used by anumber of CAD tools as an export and import option [11]. Several casestudies have shown its applicability in the design process [12,13]. Allefforts aim at the IFC becoming a standard for information exchange inthe building industry. An extensive description of generic, non-proprietary models such as the IFC can be found in [7].

Besides the generic models, software companies have developedtheir own internal models to feed their CAD and BIM software. Thesemodels differ in their structure and capabilities to establish aconsistent model. In the building industry, the concept of buildinginformation modelling has gained increasing acceptance over the lastyears. Recent developments of BIM editors are suitable to serve as fullyfunctional planning environments for architects. In our approach we

utilize the model of the proprietary modelling editor “Revit” fromAUTODESK [14]. The software enables easy establishment and editingof an extendable building information model. Its model database canbe accessed and extended by an application programming interface(API). An IFC-export and import is possible to support data exchangebetween different software packages. A model created in the softwarecan thus be exported as a generic IFC-compliant building informationmodel.

One of the goals of building information modelling is to make thecooperation between stakeholders in the building process moreefficient. This is achieved by storing relevant design information ofevery step in the design process. This ability of the model to serve as ainterdependent, multi-disciplinary data repository make newapproaches on integrating performance analysis into design possible.Parameters defined during the design process can be accessed andedited during the design process and utilized for the performancecalculation.

Even though switching to BIM-based design environments posesmajor challenges to architectural offices, recent market surveys showthat 48% of the architectural offices in the US already use methods ofbuilding information modelling [15]. Today, the biggest obstacle forarchitects to adopt BIM methods is the tentative use of BIM by otherindustry partners such as engineering firms. To be able to exploit thebenefits of BIM, the adoption of BIM in the early stages of design iscrucial. As one of the first official institutions, the U.S. General ServiceAdministration requires BIM for the submission of mayor projects forfinal concept approval. With the use of BIM, the GSA encourages“accurate energy estimates in the design process” [16], strengtheningthe adoption of BIM from the early design stages on.

3. Performance analysis

Many tools for computational performance analysis have beendeveloped, yet their application and thus their impact on the designprocess has been “rather limited” [4]. Tools for performance analysiscan be divided into two different groups, either based on a statisticcalculation model or a physical calculation model.

3.1. Physical calculation models

Physical calculation models make the precise calculation ofdetailed tasks as well as overall energy consumption possible. Fromzone loads, daylighting and solar to multizone airflow, highly precisecalculations for every possible engineering task are available. Manyexpert tools use physical calculationmodels for the calculation such asTRNSYS [17], IES Virtual Environment [18] or EnergyPlus [19]. Acomprehensive contrasting survey of software using physical modelscan be found in [20]. Necessary information input to run expertsimulations is extensive, so is knowledge to perform and interpret thesimulation results. As one of the few tools with focus on an moregraphical interface and less effort to conduct a performance analysis,Ecotect [21] is targeted at the architectural design process.

All external tools require the input of geometry of the design todefine the simulation model. This is mostly done by either importingthe geometry or manually rebuilding it in each software. Importingand exporting of building geometry is error-prone and tedious,especially as geometry models established in CAD-software areoften not suitable as simulation models. The simulation results andpossible conclusions remain in the simulation software, a feedbackinto the design software is not possible. Changes in design due toperformance criteria have to be donemanually in the design software,themodel has to be exported and simulated again. These steps have tobe repeated after every change in design. As long as a fully functionalIFC-based data exchange is not yet available, external tools utilizing aphysical calculation model for performance assessment only apply forcritical design tasks.

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3.2. Statistic calculation models

Statistic calculation models are simplified models for the estima-tion of total the energy demand, heating or lighting energy demand.Regulations such as the German Energy Savings Regulation EnEV [22]or the Swiss Minergie [2] use statistical calculation models formandatory application in the building process. Instead of calculatingthe physical processes within the building, empirically found factorsare applied. Due to their more abstract nature, these models deliverrather rough estimates, which is accepted to fulfil the regulations.Compared to the input necessary for physical models, much lessdetailed information for the calculations is needed, thus facilitatingthe parameter input. The coarser resolution also speeds up computa-tion of the results. As physical models take up to minutes and hours tocompute, statistic models deliver results in less than seconds. Even ifthe results are not highly precise, the delivered performance indicesenable judgement on building performance. Typical statistic calcula-tion tools are spreadsheet-based or even web based applications suchas IdeaXP [23].

As the goal of this approach was to realize immediate performanceassessment, a statistic calculation model for the performancecalculations was used. In order for the architect to apply in the designprocess, the effort for input and editing of parameters was tried to bekept as small as possible. This work focuses on the integration ofenergy and exergy analysis into the architectural design process.Therefore, the utilized energy and exergy calculation models are onlydescribed briefly to display which parameters are implemented andwhich results are calculated. The mathematical model applied toestimate the energy gains and losses is derived from the GermanEnergy Conservation Regulation EnEV [21]. This regulation ismandatory for the calculation of the energy demand of new andexisting buildings in Germany. The exergy calculation model devel-oped by Schmidt [27] and applied in this approach (see Section 5.) alsouses this mathematical model for the energy calculations.

4. Energy analysis

To be operated to maintain user comfort and functionality, abuilding needs a defined amount of energy that has to be supplied. Inorder to estimate the amount of energy that is needed, an energybalance has to be set up. The demand side is calculated, cumulatingenergy losses such as transmission and ventilation heat losses of thebuilding envelope. These losses can be fully or partly compensated bythe energy gains. Different sources of energy gains can be utilized.Internal energy gains caused by appliances and users as well as solargains through openings diminish the amount of heating energy thathas to be supplied. Additional energy input is needed for lighting,ventilation and for the operation of building systems. Deducting gainsfrom the overall losses results in the overall energy demandwhich hasto be delivered (Fig. 1).

Fig. 1. Implemented energy model.

Six key performance indices are calculated to display the energyperformance of the building. These indices serve as an estimate toshow the energy performance of the specific building design at themaximum temperature difference on a specified location. Most of thenecessary input parameters such as geometry andmasses, componentproperties and dependencies are automatically taken from thebuilding information model. The parameters for the design of theheating system are defined in the tool interface as described in 6.2.3.To simplify user input, some parameters of lesser impact on the overallperformance are defined as static parameters. Contrasting to theunderlying regulation, the heating energy demand is calculated forsteady state conditions. The focus is on the energy demand at amaximum temperature necessary to layout the heating system, not onthe annual energy demand the regulation aims for. Also contrasting tothe regulation, the energy demand for domestic hot water isneglected. Following key performance indices are calculated:

4.1. Transmission heat losses of the envelope

All information about the geometry of windows, walls, roofs andfloors is taken directly from the building model as well as the specificu-values of wall and window objects. Indoor (θi) and outdoor (θe)temperatures to layout the heating systems are defined by the locationof the building. The total transmission heat loss is the sum of the heatlosses of all envelope surfaces. Heat bridges are not considered.

ΦT ¼ ∑ Fx;i � Ui� Ai

�� � � θi−θeð Þ W½ � ð1Þ

The temperature correlation factor Fx,i enables using the samedesigntemperature difference for the calculation of parts facing differentenvironmental conditions. This factor is set according to the regulationsto 1.0 for exteriorwalls and roofs and to 0.6 forwalls andfloors facing theground [22]. Winter gardens, attics and unheated rooms are neglected.

4.2. Ventilation heat losses

A simplified formula captures the ventilation heat losses. Theoverall volume V is taken from the building model and multiplied bythe air exchange rate nd. The specific heat capacity of air (0.34W h/m3

K) is taken into account.

ΦV ¼ 0:34 � nd� Vð Þ � θi−θeð Þ W½ � ð2Þ

4.3. Solar heat gains through windows

The maximum amount of solar radiation is defined by thegeographic location of the building and orientation of the opening.In dependency to opening surfaces Aw,i, the solar radiation heating upthe building inside is calculated for every window. The g-value (totalsolar transmittance) of the windows defines the energy input of solarradiation passing through a specific glass.

ΦS ¼ ∑ I �s;j A �

w;i g �L;i F �

F;i F �W;i F

�C;i FS;i

� �W½ � ð3Þ

Four correction factors consider possible shading by shadingdevices (FC), shading by surrounding buildings (FS), non-orthogonalsolar radiation (FW) and window framing (FF). To simplify parameterinput, these factors are set to standard values according to theregulations, resulting in a cumulated correction factor of 0.567.

4.4. Internal heat gains

Internal heat gains caused by humans are stored as staticparameter within the occupancy parameter noo of the room. In thisapproach, the heat gain per person Φ″i,o was set to a mean values of

156 A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

80 W. It is multiplied by the statistic number of occupants. In order tosimplify parameter input, the specific heat gain by electricalappliances Φ″i,e was set as static value for all rooms. It is multipliedwith the room area. To capture different building types, this staticvalue can be adapted.

Φi;e ¼ ΦWi;e � An W½ � ð4Þ

Φi;o ¼ ΦWi;o � noo W½ � ð5Þ

4.5. Specific lighting power/lighting power

The calculation of the specific lighting power is taken from theSwiss regulation SIA 380/4 [24]. The necessary illuminance Evm ofeach room defines the specific lighting power. In relation to the type ofartificial lighting and its specific light efficiency ηV, the specificlighting power is calculated. The calculation includes factors of usageand aging ρv, for the efficiency of the lamp ηLo and a specific roomcharacteristics ηR such as reflectivity and room geometry. Thesefactors are set to standard values dependent on the type of artificiallighting in accordance to the regulations.

pLi ¼Evm � pvð Þ

ηV � ηLo � ηR� � W=m2� � ð6Þ

Resulting, the necessary lighting power is

Φi;L ¼ pLi � An W½ � ð7Þ

The specific lighting power is also added to the internal heat gains.Additionally, the auxiliary electrical energy for ventilation based onthe internal volume is calculated and added to the total electricalenergy consumption.

4.6. Resulting heat demand

All heat flows including gains and losses are summed up to createthe heating energy balance:

heat demand ¼ sum of heat losses−sum of heat gainsΦh¼ ΦT þΦVð Þ− Φs þΦi;o þΦi;e þΦi;L

� �W½ �: ð8Þ

5. Exergy analysis

The common definition of energy utilization refers to the first lawof thermodynamics which states that energy is stored in every deviceand process and can neither be consumed nor destroyed; it can onlybe transformed [25]. For a more detailed analysis of energy flows inbuildings, this concept is “inadequate for depicting some importantaspects of energy resource utilization” [25]. In other words, it is not

Fig. 2. The heating chain as modelled for th

precise enough. In order to describe energy flows in buildings, theconcept of exergy was introduced by Shukuya [26]. To understand thethermodynamic concepts of exergy and its counterpart, entropy, thefollowing description of an environmental control system for build-ings, such as a heating, can be assumed:

In order to maintain comfortable indoor temperatures, energyand mass have to be supplied. In the case of a heating system,assuming steady state conditions, heat transmission occurs from thewarm inside to the cold outside of the environment. If assumed thatthe energy is only transformed it should be possible to directly reusethe energy [27]. However, the potential of the reusable energy issmaller than at the point of input, the system “discards something”[27]. The constant flow of energy from the warm inside of a buildingto the cold outside results in increasing flow of entropy on the waythrough the building envelope [28]. The concept of exergy quantifiesthe potential of an energy source to be dispersed. The concept ofentropy helps to quantify the state of dispersion of the energysource.

Unlike energy, exergy can be lost by decreasing the potential of anenergy source to do work. This can be illustrated with a simpleexample [25]: Within an enclosure, a combustion process is used toheat upwater for the heating. An exergy source such as fuel, deliveringa temperature of 900 °C, heats up the water to a maximumtemperature of 60 °C. Only a small amount of the heat delivered isused to heat the water, the rest diffuses into the surroundingenvironment. According to the first law of thermodynamics, theinitial amount of energy within the enclosure is still the same. Whenthe fuel has been burnt, the potential of the water and the slightlywarmer environment to do further work is much lower than thepotential of the fuel that was used. The potential has been destroyed,exergy has been lost. Exergy can therefore also be described as the“valuable part of energy” [27]. The method of exergy analysis can beused to “guide efforts to reduce sources of inefficiency in existingsystems” [25]. To analyse the systems, an integrated view on thebuilding is necessary. This integrated view must include buildinggeometry, construction and technical systems, making multi-dis-ciplinary information of the building design crucial.

Most of the energy used in buildings is used to maintaincomfortable room temperatures. Heating consumes up to 57% of abuildings total energy demand [1]. High-potential energy sources(exergy) and low potential energy sources found in the environmentcan be used to generate heating energy. Low potential sources such asoutside air or geothermal heat are infinitely available. When theheating chain is designed according to the optimal utilization of a lowpotential source, for example to drive a heat pump, exergy obtainedfrom sources such as fossil fuels can be reduced. Because of theinfluence of building form, construction and technical systems on theexergy consumption of a building, the consideration of exergy resultsin more flexibility for the building designer to choose optimizationmeasures. The common term of “saving energy” therefore has to be

e energy calculations ([27], modified).

Fig. 3. Implementation setup.

157A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

redefined; not energy but exergy efficiency is important to reduce CO2

emissions.

5.1. Energy/exergy calculations of the heating chain

In order to calculate the exergy flow through the heating chain, theenergy flow has to be estimated first. As heating energy is transformedfrom heat generation to emission into the room, losses at each of thesteps occur. The sum of losses defines the overall heating energydemand to be supplied by primary energy which is transformed fromfossil or renewable energy sources. In accordance to the DIN 4701-10[29], the analysis of the heating chain starts at the generation of theprimary energy. When the supplied energy passes through the steps,the occurring losses are dependant on factors such as construction ofthe envelope and choice of heating systems components.

At the building level, all components influencing the heating chainsuch as building geometry, construction and choice of systems areconsidered for the analysis. The subsystems of the heating chain canbe separated into six steps. For each step, additional input parametersfor the building service systems are defined according to Schmidt [27].These input parameters are automatically set due to the combinationof the subsystems the user chooses in the interface. A detailed list ofthe input parameters can be found in Appendix A.

The energy and exergy calculations of the heating chain have to beperformed in the opposite direction of the development of the heatdemand as shown in Fig. 2. The demand of each subsystem must besatisfied by the subsystem before. Following, the calculations for eachstep are briefly described in accordance to the model developed bySchmidt [27]:

5.1.1. Envelope subsystemThe total heat demand as calculated in the energy calculations is

most important for the first step. The exergy demand of the room isestimated by multiplying the heat demand with the quality factor ofthe room Fq,room. This quality factor is estimated by the Carnotefficiency using the outside and inside temperature of the room. Thenthe exergy demand to be satisfied is:

Exroom ¼ Φh� Fq;room W½ � ð9Þ

5.1.2. Room air subsystemThe room is heated by a warm surface. The temperature difference

between the heated surface and the room temperature defines theexergy content. With the estimation of the surface temperature of theheater, a new quality factor of the heater surface Fq,heat is alsocalculated by the Carnot efficiency using the temperature of the heater

surface and the outside temperature. This factor is then multipliedwith the heat demand of the building.

Exheat ¼ Φh � Fq;heat W½ � ð10Þ

5.1.3. Emission subsystemFirst the heat losses of the emission subsystem Φloss,E have to be

calculated by taking the efficiency of the chosen emission system intoaccount. Then the exergy load of the emission system is estimated inrelation to inlet (Tin), return (Tret) and outside (To) temperatures.

ΔExemis ¼Φh þΦloss;E� �

Tin−Tretð Þ � Tin−Tretð Þ−To � ln TinTret

� �W½ � ð11Þ

The exergy demand after the emission systems is:

Exemis ¼ Exheat þ ΔExemis ð12Þ

5.1.4. Distribution subsystemThe exergy demand of the distribution subsystem is calculated

similar to the emission subsystem. First, its heat losses are calculated.The mean design temperature Tdis is used as inlet temperature, thereturn temperature is the design temperature minus the temperaturedrop ΔTdis.

ΔExdis ¼Φloss; D

ΔTdis� ΔTdis−To � ln

TdisTdis−ΔTdis

� �W½ � ð13Þ

The exergy demand after the distribution systems is:

Exdis ¼ Exemis þ ΔExdis W½ � ð14Þ

5.1.5. Storage subsystemThe exergy demand of the storage subsystem is calculated similar

to the distribution subsystem. First, the heat losses are calculated. Thistime, the mean design temperature Tsto is used as inlet temperature,the return temperature is the design temperature minus thetemperature drop ΔTsto.

ΔExsto ¼ Φloss;S

ΔTsto� ΔTsto−To � ln Tdis þ ΔTdis

Tdis þ ΔTdis−ΔTsto

� �W½ � ð15Þ

The exergy demand after the storage systems is:

Exsto ¼ Exdis þ ΔExsto W½ � ð16Þ

Table 1Additional parameters to be added to the building model

Component Parameter Type

Room Illumination SemanticOccupancy SemanticLighting Semantic

Wall u-value SemantictoRoom Topological

Window u-value Semanticg-value SemanticOrientation TopologicaltoRoom Topological

158 A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

5.1.6. Generation subsystemThe generation subsystem has to satisfy the demand of all

subsystems. A possible seasonal storage utilizes thermal solar powerwith a solar fraction Fs. The requested energy of generation therefore is

ΦGe ¼ Φh þΦloss;E þΦloss;D þΦloss;S� �� 1−Fsð Þ� 1

ηGW½ � ð17Þ

The generation system is supplied with an energy carrier with apre-defined quality factor Fq,S. This factor is based from “statisticalmaterial and political discussion” [27] and evaluates the qualities ofdifferent energy sources. In this case it is set to 1.0 (Germany). Thetotal exergy load therefore is:

ExGe ¼ ΦGe � Fq;S W½ � ð18ÞIn addition, the exergy load of other building service components

such as lighting Pl and ventilation PV is calculated, multiplied by thequality factor and added to the total exergy demand of the building.

Explant ¼ Pl þ PVð Þ�Fq;electricity W½ � ð19Þ

5.1.7. Primary energy transformation subsystemThe required primary energy inputs are defined by the calculated

overall energy and exergy loads. It can be differentiated betweenrenewable and non-renewable parts. The primary energy factor Fp and

Fig. 4. Modeller wit

a fraction factor to divide the fossil part from the renewable part Frenewmust be given. In this case, Fp is set to 3.0 (Germany). The non-renewable part can be calculated as follows:

Eprim;tot ¼ ΦGe � Fp þ Pl þ PV þ ∑Pauxð Þ�Fp;electricity W½ � ð20Þ

If an heat source Eenvironment is utilized to extract heat from theenvironment, the additional renewable part can be calculated:

Erenew ¼ ΦGe � Frenew þ Eenvironment W½ � ð21Þ

5.1.8. Results of the exergy calculationsThe exergy calculation results are displayed by two performance

indices which show overall and specific exergy utilization.

5.1.8.1. Total exergy load. This index shows the total amount of exergynecessary to supply the building. The total exergy load is dependenton building construction, geometry and system selection. Optimiza-tion can be achieved by balancing between these three different fields.The total exergy load of the building is:

Extot ¼ ΦGe � Fp � Fq;S þ Pl þ PV þ ∑Pauxð Þ�Fp;electricity þ Erenew� Fq;renew W½ � ð22Þ

5.1.8.2. Total exergy system efficiency. Dividing the remaining exergythat leaves the room through the envelope by the total exergy load ofthe room results in an exergy system efficiency index. It displays theratio of exergy that is actually used to heat the room.

Exeff ¼ExroomExtot

� ð23Þ

6. Implementation: The Design Performance Viewer (DPV)

The mathematical models for energy and exergy calculation areimplemented into the software code. Necessary parameter values for

h tool interface.

Fig. 5. Building Data tab.

Fig. 6. Performance tab with Kiviat diagram.

159A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

the calculations are accessed directly from the building modeldatabase. In order to access the model database, the suppliedapplication programming interface (API) of the model editor isutilized. The API can be addressed using a .NET [30] programminglanguage such as Visual Basic or C#. Applying the concept of object-oriented programming, the software is organised in classes such ascalculation and visualization classes. The focus of the implementationwas on speed of calculation and fast and intuitive display of results. Inorder to serve as a design support tool accepted by the buildingdesigner, the results have to be calculated and visualized in quasi real-time (Fig. 3).

The building model of a specific design is established in theeditor. Once the necessary parameters are set, the DPV is started asan external application out of the editor. During the designprocess, the user can switch between the calculations andvisualization in the tool interface and the building model of hisdesign. Alongside the progression of the building design, theresulting performance can be assessed at any time. Additionalimport or export procedures or manual data entry is not necessary(Fig. 4).

6.1. Model parameterization

All geometry data such as areas and volumes is automatically takenfrom model geometry. For the energy and exergy calculations, nineadditional parameters have to be added to the object properties ofrooms, walls and windows (Table 1).

These parameters have to be added once at the beginning ofthe modelling process. During the design only the parameter

values have to be adapted, all geometry data is updatedautomatically. In addition to the these parameters some namingconventions have to receive attention, such as the correct namingof the levels.

The input parameters for the energy/exergy calculations of theheating chain (see Section 5.1) are automatically set by choosing thepreferred heating chain components in the interface. These systemspecific parameters are embedded into the program code and notstored in the building model.

6.2. Tool interface and visualization

The tool interface addresses the architect and building designerwho has to make conceptual and design decisions already in anearly stage of his design. The amount of necessary inputparameters was to be kept as small as possible without sacrificingthe significance and plausibility of the results. As many parametersas possible are directly read out of the building information model.Of the five different interface tabs, only one—the “Systems” tab—needs user input to choose the subsystems of the heating chain.The subsystem selections are labelled in a way an architect canrelate to them, such as “boiler” or “radiator”. The resulting inputparameters are automatically set according to the combination ofsubsystems as some parameters influence parameters of othersubsystems.

Another important aspect is the visualization of the results. Forfast and intuitive comprehension, it is not sufficient to display theresults how this is commonly done in simulation software—in

Fig. 7. Building footprint of initial (left) and optimized design (right).

Fig. 8. System selection tab.

160 A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

endless rows of numbers. Fast visual feedback is necessary for quickinterpretation of the results; suitable graphical visualisation has tobe implemented.

6.2.1. Building DataThe first interface tab “Building Data” (Fig. 5) shows extractions

from the geometry model and provides information important for thearchitect such as opening surface ratio or orientation ratio of thewindows. This information is graphically represented by a bar chart.The tab also displays the calculated average u- and g-values of wallsand windows.

6.2.2. PerformanceThe “Performance” tab (Fig. 6) displays selected energy perfor-

mance indices and visualizes the calculated results in a Kiviat diagram.Kiviat diagrams are common in computer performance evaluation[31] and can also be found in economic [32] and environmentalinformation visualization. The values of the performance indices areplotted onto their individual axis. Connecting the nodes creates adistinct shape, the “building performance footprint”. Changes of theshape can be easily linked to changes in building design. For fast visualjudgement of the performance of design alternatives, their specificshapes can be compared (Fig. 7).

6.2.3. Systems SelectionThe tab “Systems Selection” (Fig. 8) is the only part of the

interface where user input is required. The building designer canchoose the component of the heating chain he prefers, fromgeneration of heating energy to storage, distribution and emission.According to the selections in the pull-down menus, differentsystem values such as the system efficiency, supply and returntemperatures are automatically set. Additionally, the design tem-peratures of the heating system, the outside and inside tempera-tures, can be altered, defining the environmental conditions. Thesevalues are used to define the conditions for the energy and exergyanalysis of the heating chain.

6.2.4. Energy/ExergyThe “En/Ex Balance” tab (Fig. 9) displays results and visualizations

of the energy and exergy flows of the current building and heatingsystem design. An automatically generated Sankey diagram is used to

visualize the energy flows by components. Arrows of differentdirection and strength show losses and gains of individual buildingcomponents. The energy balance shows which components account

Fig. 9. Energy/exergy balance tab.

161A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

to which percentage to the energy loss of the building and whichsources contribute to the energy gains (Fig. 10).

Below the Sankey diagram, the exergy bar graph displays theexergy performance indices: For each step of the heating chain theexergy losses are calculated and displayed. It shows how exergy is

Fig. 10. Sankey diagrams of design with di

utilized throughout the steps of the heating chain. The exergyefficiency index shows the percentage of exergy that is actually usedto heat the rooms. The total amount of exergy required for thespecific building is displayed as “Demand” under the first bar of thebar graph.

Finally, the “Data” tab lists all executed energy and exergycalculations and the extracted parameter values. This tab can beviewed for the detailed results.

7. Results and discussion

The prototypical tool DPV enables balancing between possiblemeasures to increase overall building performance. The results fromthe calculations of the simplified energy model implemented werecompared to the results of a commercial and certified software [33]which is used to verify the conforming of the EnEV regulation. Theresults show variations below 5%, proving the sufficiency for theproposed early stage performance assessment. In contrast to thesoftware used for the comparison, the assessment of the perfor-mance analysis of a specific building takes only a few seconds usingthe DPV. In addition to the calculation of total energy and exergydemands, the building designer can decide which optimizationmeasure is most suitable for the concept and context of the building.Most important, balancing between form, materialization andtechnical systems is possible from the beginning on. If, for example,the façade cannot be altered, a better heating system using adifferent energy source can be chosen. If, for another example, a slabheating is desired, a certain setup of the heating system is necessary:Due to the smaller heat exchange rate of the slab heating, low heatlosses are required. These can be achieved by choosing a goodenvelope insulation and/or a mechanical ventilation. Also, solar gainscan be used to heat up the rooms. In order to increase solar gains,the opening surfaces should be increased and the g-values of theglass should be adapted.

Utilizing building information modelling to realize fast energyand exergy performance assessment opens up the possibility of amore integrated view on buildings during their early design stages.The parameterized model enables capturing the complexity result-ing from manifold dependencies of building components andenvironment. Implementing the concept of exergy proved tomake more precise definitions of efficiency in building possible. Itenables balancing between different qualities of energy for

fferent energy supply configurations.

162 A. Schlueter, F. Thesseling / Automation in Construction 18 (2009) 153–163

different purposes. The concept of “low-exergy” [34]—to optimizethe use of the part of high-potential energy—offers more flexibilityfor the building designer to choose appropriate measures for anoptimization. If, for example, a façade cannot be altered due toconservatory reasons, the exergy demand can be reduced bychoosing appropriate technical systems utilizing renewablesources. This also applies to new buildings: if a renewable energysource such as geothermal heat is available, higher transmissionheat losses of the envelope caused by a certain façade design can becounterbalanced. In such a case, the energy demand would be highbut the exergy demand responsible for the CO2 emissions wouldstay low. Only a fraction of high-potential energy, the exergy, isnecessary to drive the heat pump for heat generation. Due to themore precise view on the different qualities of energy and theresulting increase of flexibility for the building designer, theconcept of low-energy should be replaced by the more precisedefinition of low-exergy.

Intuitive parameter input and instantaneous calculations areimportant for performance assessment playing an equal role in thedesign process. However, these simplifications have to lead tocorrect calculation results. In this approach, the fast calculation isachieved by using a statistical mathematical model. The modeldoes not include dynamic calculations over a certain time periodand simplifies certain input parameters. It cannot be used tosimulate the annual energy demand of the building. However, itshows tendencies and estimates necessary to make designdecisions and to communicate them. In professional application,the tendencies shown by the DPV would have to be supplementedby simulations offering a higher resolution. Important however isthat tendencies how good a design performs can be discovered andconsidered to make design decisions. Further work on the DPV isdedicated to include dynamic calculations of energy demands bykeeping the immediate output of the results. A first case study incontext of the “ViaGialla” concept [35], carried out with 27 studentsof architecture at ETH Zürich has shown that the DPV is suitable tointegrate performance criteria into design decision-making. In twoworkshops, the students used the DPV from the beginning of theirdesigns. The introduced editor made easy establishment andparameterization of the building information model possible.Students were able to evaluate their designs by using the DPV. Insome cases, these evaluations had strong effects on their design,some students chose to give performance aspects less considera-tion. But all students became aware of the dependencies andpossible measures to design energy/exergy efficient buildings.Intuitive visualization of the results to enable easy and quickinterpretation proved to be very important and has to be carriedeven further.

Computer based methods are used in an impressing andexciting way in various fields of architecture such as advancedgeometry and computer-aided production methods. New toolsmake it possible to design and actually build forms that would notbe possible without the use of computers. These powerful methodshave to be applied to actually design better building, not onlybetter looking ones. Incorporating building performance analysisinto the design process utilizes the full potential of computationalmethods in architecture. To capture the complex dependencies,to view the building as a system makes new approaches inarchitecture possible. These approaches have to be furtherexplored.

Acknowledgements

The authors wish to acknowledge Prof. Dr. Hansjürg Leibund-gut, Forrest Meggers and Luca Baldini for their inspiration andsupport in research and implementation of the energy and exergymodels.

Appendix A. System selections and input parameters of theheating chain

System parameters generationSystems

1. Condensing boiler 2. Heat pump water/glycol

System variables

Unit Efficiency ηG/COP –

Primary energy factor source FP

–

Quality factor of source Fq,S

–

Max. supply temperature θS,max

°C Auxiliary energy paux,ge W/kWheat

Auxiliary energy paux,ge,const

W Part. environmental energy Frenew –

System parameters storage

1. No storage 2. Small/day storage 3. Seasonal storage

System variables

Unit Heat loss/efficiency ηG –

Auxiliary energy paux,S

W/kWheat

Solar fraction FS

–

System parameter distribution

Subsystem Selection 1. Boiler position inside/outside/no distribution 2. Insulation no/good/bad insulation 3. Design temperature lowb35 °C/middleb50 °C/high (other) 4. Temperature drop lowb35 K/middleb50 K/high (other)

System variables

Unit Heat loss/efficiency ηD –

Auxiliary energy paux,ge

W/kWheat

System parameters emission

Systems 1. Floor heating 2. Radiator 3. Ceiling heating 4. Slab heating

System variables

Unit Inlet temperature θin °C Return temperature θret °C Auxiliary energy paux,E W/kWheat

Max. heat emission pheat,max

W/m2

Heat loss/efficiency ηE

–

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