NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

IEA BESTEST Multi-Zone NonAirflow In-Depth Diagnostic Cases

Preprint

J. Neymark

J. Neymark & Associates

R. Judkoff

National Renewable Energy Laboratory

D. Alexander

Cardiff University

C. Felsmann

Dresden University of Technology

P. Strachan

University of Strathclyde

A. Wijsman

VABI Software

To be presented at the Building Simulation 2011 Conference

Sydney, Australia

November 14-16, 2011

Conference Paper

NREL/CP-5500-51589

November 2011
NOTICE

The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC 

(Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US 

Government and Alliance retain a nonexclusive royalty-free license to publish or reproduce the published form of 

this contribution, or allow others to do so, for US Government purposes.

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, 

express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of 

any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately 

owned rights. Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, 

or favoring by the United States government or any agency thereof. The views and opinions of authors 

expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy

and its contractors, in paper, from:

U.S. Department of Energy

Office of Scientific and Technical Information

P.O. Box 62

Oak Ridge, TN 37831-0062

phone: 865.576.8401

fax: 865.576.5728

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from:

U.S. Department of Commerce

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone: 800.553.6847

fax: 703.605.6900

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/help/ordermethods.aspx

Cover Photos: (left to right) PIX 16416, PIX 17423, PIX 16560, PIX 17613, PIX 17436, PIX 17721

Printed on paper containing at least 50% wastepaper, including 10% post consumer waste.
 

 

 

 

 

 

 

 

 

 

 

 

 

 

IEA BESTEST MULTI-ZONE NON-AIRFLOW IN-DEPTH DIAGNOSTIC CASES 

J. Neymark1

and R. Judkoff2
 

With
 

D. Alexander3

, C. Felsmann4, P. Strachan5, A. Wijsman6 

1

J. Neymark & Associates, Golden, Colorado, U.S. 

2

National Renewable Energy Laboratory, Golden, Colorado U.S.

3

Cardiff University, Cardiff, Wales, U.K.
 4

Dresden University of Technology, Dresden, Germany

5

University of Strathclyde, Glasgow, Scotland, U.K. 

6

VABI Software, Delft, The Netherlands
 

ABSTRACT 

A set of in-depth diagnostic test cases for multi-zone 

heat transfer was developed. These are designed to 

test the ability of building energy analysis tools to 

model multi-zone conduction, multi-zone shading, 

including automated building self-shading and 

modeling of internal windows between zones. A 

methodological advancement for this work, which 

enhances the diagnostic capability of the tests, is that 

the multi-zone shading and internal window test 

cases were specified using building zones designed to 

be modeled as precise calorimeters. The basic 

principle is that all solar radiation incident on an 

exterior window is captured within a zone, such that 

the zone cooling load is equivalent to the solar 

radiation incident on that window. 

INTRODUCTION 

This paper documents a set of in-depth diagnostic 

test cases for multi-zone heat transfer models that do 

not include the heat and mass transfer effects of 

airflow between zones. The multi-zone non-airflow 

test cases represent an extension to IEA BESTEST 

(Judkoff and Neymark 1995a). This new work was 

conducted by the National Renewable Energy 

Laboratory (NREL), United States, in collaboration 

with a working group of international experts under 

International Energy Agency (IEA) Solar Heating 

and Cooling (SHC) Programme Task 34 and IEA 

Energy Conservation in Buildings and Community 

Systems (ECBCS) Programme Annex 43 (IEA 

34/43). 

Background: Building Energy Simulation Test 

and Diagnostic Method (BESTEST) 

NREL has developed a number of building energy 

simulation test (BESTEST) suites for evaluating and 

diagnosing errors in software used for energy 

analysis of commercial and residential buildings. 

ASHRAE Standard 140, Standard Method of Test for 

the Evaluation of Building Energy Analysis 

Computer Programs (ASHRAE 2007), either 

adopted the BESTEST test suites or are in the 

process of adopting them. Many entities have 

adopted or cited Standard 140 and/or the component 

BESTEST suites: the Internal Revenue Service 

(2008) (for certifying software used to determine tax 

deductions), ASHRAE building energy efficiency 

Standards 90.1 and 189.1 (ANSI/ASHRAE/IESNA 

2007, ANSI/ASHRAE 2009), RESNET (2006, 

2007), COMNET (Eley 2011), the International 

Energy Agency (Judkoff and Neymark 2009), and 

the European Community under its Energy 

Performance Directive (European Union 2002). 

These methods include software-to-software 

comparative testing, verification versus analytical 

solutions, and validation versus vetted empirical 

data. The theoretical basis for the BESTEST 

procedures is further described in the literature 

(ASHRAE 2009, Judkoff 1988, Judkoff et al. 2008, 

Judkoff and Neymark 2006). 

Importance of the Multi-Zone Modeling Problem 

Many buildings have multiple mechanical equipment 

control zones, and are therefore better modeled with 

multiple zones. Additionally, architectural features 

related to shading or that use internal windows are 

often applied in a multi-zone context. For example, a 

shading device associated with one zone of a model 

may cast a shadow on a window or wall associated 

with another zone of that model. 

Current IEA BESTEST building thermal fabric test 

cases originally published by NREL in 1995 (Judkoff 

and Neymark 1995a, ASHRAE 2007) test the ability 

to model the thermal physics related to many typical 

building features such as thermal mass, windows, 

shading devices, orientation, internal gains, 

mechanical ventilation, and thermostat set point 

variation. These test cases are applied in a singlezone modeling context, except for one test case for 

modeling a sunspace that interacts with a conditioned 

zone via a common wall. HERS BESTEST (Judkoff 

and Neymark 1995b), also published by NREL, is 

designed to similarly test simplified tools commonly 

used with residential modeling. These test cases 

provide a more realistic, but less diagnostic context 

1
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

than IEA BESTEST (Neymark and Judkoff 1997). 

HERS BESTEST includes the possibility for (but 

does not require) multi-zone modeling in all of its 

cases for an unconditioned attic, and in two of its 

cases that include a basement. However, the HERS 

BESTEST output requirements do not disaggregate 

results for separate zones, which inhibits multi-zone 

modeling diagnostics. 

If a model has good agreement for the current set of 

building thermal fabric test cases that emphasize 

single-zone modeling, phenomena specific to multizone configurations are not necessarily being 

correctly modeled. 

Additional work published during IEA SHC Task 

12/ECBCS Annex 21 by Tampere University of 

Technology (Haapala et al. 1995) developed six 

test cases in a realistic commercial building/multizone context using two conditioned zones 

separated by a conditioned or unconditioned 

corridor zone, where only walls with windows are 

exposed to ambient conditions. NREL reviewed 

this work and observed the following (Neymark et 

al. 2008): 

	 Although the cases use a multi-zone 

configuration, multi-zone modeling effects are 

not well isolated. 

o	 The only discernible multi-zone modeling 

observation was that an unconditioned 

corridor caused disagreement among 

simulation results to expand, versus a 

conditioned corridor. 

o	 Other than that, because of many 

simultaneously acting phenomena, it was 

difficult to make specific conclusions 

Figure 1 Multi-zone conduction schematic (Neymark 

et al. 2008) 

Internal Walls 

Zone A Zone C 

Set Point 15°C Cooling 

Only 

Set Point OFF (floating) 

Internal Gains = OFF 

6 m 6 m 

8 m 

0.15 m 0.15 m 

Zone B 

Set Point OFF (floating) 

6 m 

Internal Gains = 2500 W Internal Gains = 1000 W 

Figure 2 Multi-zone shading schematic (Neymark et 

al. 2008) 

6 m 

6 m 

6 m 

8 m 

5 m 

5 m 

Not to Scale 

Zone D 

Zone E 

Zone A 

Zone B 

Zone C 

N 

Zone F 

Shading Fin 

5.0 m 

24 m 

1.0 m 

regarding multi-zone interactions. 

	 No found bugs were documented for the 

simulation programs that ran the field trials of 

these early stage multi-zone test cases, whereas 

several found bugs were documented and fixed 

during field trials of the IEA BESTEST singlezone test cases that were also developed during 

IEA SHC Task 12. 

As none of the test suites described above adequately 

isolates phenomena specific to multi-zone modeling, 

test cases were developed to address such 

phenomena. 

THE IEA 34/43 MULTI-ZONE NONAIRFLOW DIAGNOSTIC TEST CASES 

A set of five diagnostic test cases for multi-zone nonairflow heat transfer models were developed. The test 

cases cover modeling of: 

 Interzonal conduction heat transfer, assuming 

one-dimensional conduction (see Figure 1) 

 Multi-zone shading, including building selfshading (see Figure 2) 

 Internal windows between zones (see Figure 3). 

Figure 3 Multi-zone internal window schematic 

(Neymark et al. 2008) 

12 m 

Not to Scale 

12 m 

Zone C 

Zone B 

Zone A 

N 

45° 

2
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We began the test cases by developing a relatively 

simple steady-state analytical solution (analytical 

verification test) for multi-zone conduction. Good 

agreement between simulation program results and 

the multi-zone conduction analytical solution was 

obtained early in the project. This provided a good 

starting point for developing diagnostic comparative 

test cases that test multi-zone shading models and 

internal window models. 

We specified the multi-zone shading and internal 

window test cases by using idealized building zones 

designed to be modeled as precise calorimeters, 

where the only thermal mass is that of the zone air. 

The basic principle is that all solar radiation incident 

on an exterior window is captured within a zone, 

such that the zone cooling load is equivalent to the 

solar radiation incident on that window. Causes of 

disagreements are therefore limited to either an issue 

with the specific model being tested (the shading or 

internal window model), modeling of incident solar 

radiation, inability to precisely model the 

idealizations defining the zone as a calorimeter, or an 

input error. Additionally, sensitivity “delta” cases 

allow intermodel comparison of the difference 

between zone cooling loads with a shading device 

and without shading. This allows better isolation of 

shading model effects, as differences among models 

not related specifically to shading models should 

cancel out. 

The effects of thermal mass were not tested in these 

new cases because the original IEA BESTEST 

(Judkoff and Neymark 1995a) comparative cases 

explored building envelope thermal mass effects in 

detail in a single-zone context (and in a two-zone 

case with a sunspace). By excluding thermal inertia 

and minimizing other simultaneous effects, the 

current specialized multi-zone cases maximize 

diagnostic power, and also minimize the number of 

cases required to address the tested phenomena. In 

the absence of multi-zone mass interaction test cases 

for the current configurations, if a simulation model 

demonstrates agreement for the original IEA 

BESTEST cases with thermal mass and demonstrates 

agreement for the new multi-zone test cases, this 

would suggest that such tested simulations may 

provide agreement where aspects of both types of test 

cases are combined. As thermal mass interactions 

(and other interactions) are important to test 

explicitly, our recommendations for future activities 

include developing multi-zone cases with thermal 

mass. 

RESULTS 

Field trials of the new IEA BESTEST cases were 

conducted with a number of detailed state-of-the-art 

whole-building energy simulation programs from 

around the world, including: 

 For all cases: EnergyPlus (2008), ESP-r (2008), 

HTB2 (2008), TRNSYS-16 (2005), TRNSYSTUD (2008), VA114 (2008) 

 For conduction only: CODYRUN (2005), 

COMFIE (Peuportier and Sommereaux 1994), 

KoZiBu (2005). 

The simulation-trial process was iterative in that 

executing the simulations led to refinement of the 

BESTEST cases, and the results of the tests led to 

improving and debugging the models. Improvements 

to simulation programs or simulation inputs made by 

participants must have a mathematical and a physical 

basis, and must be applied consistently across tests. 

Arbitrary modification of a simulation program’s 

input or internal code just for the purpose of more 

closely matching a given set of results is not allowed. 

All improvements were required to be documented 

and justified in modeler reports, which are included 

in the final report (Neymark et al. 2008). 

The multi-zone conduction case is a steady-state 

system of three zones in series with a conditioned zone 

on one end adjacent to two adjacent unconditioned 

(free floating temperature) zones, where the interior 

and exterior walls are conductive (see Figure 1). This 

case has a relatively simple analytical solution, as 

documented in the final report. For the Zone C cooling 

load all models tested agreed with the analytical 

solution within 0.3% except for one program 

(CODYRUN), which is within 1.9%. 

For the multi-zone shading and internal window test 

cases, improvements to the simulation programs are 

evident when initial results are compared to final 

results, as shown in Figures 4 and 5, respectively, for 

the multi-zone shading cases, and Figures 6 and 7, 

respectively, for the internal window cases. These 

results indicate that there was initially 20%–90% and 

40%–155% disagreement among annual cooling 

loads for various zones for the multi-zone shading 

and internal window cases, respectively, with 

substantial scatter among the programs. Here, 

disagreement is the difference between the maximum 

and minimum results for each case, divided by the 

mean of the results for each case ((max-min)/mean). 

After correcting software and modeling errors using 

BESTEST diagnostics – there were 31 fixes 

documented during the simulation trials – the 

remaining disagreements among results for various 

zones for multi-zone shading are 5%–13%, and for a 

single internal-window configuration are 7%–34%. 

For the most challenging configuration of the internal 

window cases, with a second internal window in 

series, disagreement for annual cooling load for the 

zone located interior to the second internal window is 

112% (see bars for Zone C in Figure 7), thus 

indicating further refinement of models for this 

configuration may be warranted. Scatter among 

results was reduced for all the cases. 

3
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0 

3000 

6000 

9000 

12000 

15000 

0 

15000 

IEA BESTEST Multi-Zone: MZ340, MZ350, MZ355 

Annual Sensible Cooling Load, All Zones IEA BESTEST Multi-Zone: MZ360 

Annual Sensible Cooling Loads 

140000 

120000

Sensible Cooling Load (kWh) 

Sensible Cooling Load (kWh) Sensible Cooling Load (kWh) 

100000 

80000 

60000 

40000 

20000 MZ340 MZ350, MZ350, MZ350, MZ350, 

MZ355 MZ355 MZ355 MZ355 MZ350 MZ350 

Zone B Zone E Zone A Zone D Zone C Zone F
 

0 

Building, Zone A, Zone B, Zone C, QB + QC 

Qbldg QA QB QC 

HTB2/WSA TRNSYS-TUD/TUD 

TRNSYS-16/ULg ESP-r/ESRU 

VA114-CirBm/VABI VA114-CirDf/VABI 

EnergyPlus/GARD VA114-CirBm-MZ355/VABI 

VA114-CirDf-MZ355/VABI EnergyPlus-MZ355/GARD 

HTB2/WSA TRNSYS-TUD/TUD TRNSYS-16/ULg 

ESP-r/ESRU VA114-CirBm/VABI VA114-CirDf/VABI 

EnergyPlus/GARD 

Figure 4 BESTEST multi-zone shading cases – 

sensible cooling load, before BESTESTing 

(Abbreviations along the x-axis are shorthand for the 

case descriptions, see Nomenclature; building selfshading results are three rightmost bars for zones B, 

E, A, and D.) (Neymark et al. 2008) 

IEA BESTEST Multi-Zone: MZ340, MZ350, MZ355 

Annual Sensible Cooling Load, All Zones 

Figure 6 BESTEST internal windows – sensible 

cooling load, before BESTESTing (Abbreviations 

along the x-axis are shorthand for the output 

descriptions; see Nomenclature.) (Neymark et al. 

2008) 

IEA BESTEST Multi-Zone: MZ360 

Annual Sensible Cooling Loads 

140000 

Building, 

12000 

9000 

6000 

3000 

Sensible Cooling Load (kWh) 

120000 

100000 

80000 

60000 

40000 

20000 

MZ340 MZ350, MZ350, MZ350, MZ350, 0 MZ355 MZ355 MZ355 MZ355 MZ350 MZ350 Zone A, Zone B, Zone C, QB + QC Zone B Zone E Zone A Zone D Zone C Zone F Qbldg QA QB QC 

HTB2/WSA TRNSYS-TUD/TUD 

TRNSYS-16/ULg ESP-r/ESRU 

VA114-CirBm/VABI VA114-CirDf/VABI 

EnergyPlus/GARD VA114-CirBm-MZ355/VABI 

VA114-CirDf-MZ355/VABI EnergyPlus-MZ355/GARD 

Figure 5 BESTEST multi-zone shading cases – 

sensible cooling load, after BESTESTing 

(Abbreviations along the x-axis are shorthand for the 

case descriptions, see Nomenclature; building selfshading results are three rightmost bars for zones B, 

E, A, and D.) (Neymark et al. 2008) 

Improvements in Shading Diagnostics Versus 

Previously Published Test Cases 

Improvement in the ability to diagnose shading 

models is evident from comparing final disagreement 

HTB2/WSA TRNSYS-TUD/TUD TRNSYS-16/ULg 

ESP-r/ESRU VA114-CirBm/VABI VA114-CirDf/VABI 

EnergyPlus/GARD 

Figure 7 BESTEST internal windows – sensible 

cooling load, after BESTESTing 

(Abbreviations along the x-axis are shorthand for the 

output descriptions; see Nomenclature.) (Neymark et 

al. 2008) 

disagreement is 38%–73% for the absolute results 

(cases considered alone), and 46%–63% for the delta 

results (sensitivity results to isolate shading model 

effects, e.g., Case 630–620) (ANSI/ASHRAE 2007; 

Judkoff and Neymark 1995a). A graphic example of 

original single-zone shading case disagreement in the 

delta context, excerpted from IEA BESTEST, is 

ranges for the original single-zone IEA BESTEST 

shading cases for more realistic constructions, versus 

the final range of disagreement for the new in-depth 

diagnostic multi-zone shading cases. For the more 

realistic original single-zone cases with shading 

devices, the range of annual cooling load 

provided in Figure 8. Disagreement ranges for final 

delta results of the current multi-zone cases are 

smaller relative to mean sensitivities (see Figure 9), 

ranging from 5%-6% for shading by the front side of 

the fin (zones B, E, A, D) to 20%-21% for the back 

side of the fin (zones C, F). 

4
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 8 IEA BESTEST single-zone east- and westshaded window delta sensitivity, annual heating and 

sensible cooling loads (Judkoff and Neymark 1995a) 

IEA BESTEST Multi-Zone: MZ350-MZ340, MZ355-MZ340
 

Delta Annual Cooling Load, All Zones
 

0 

-1000 

-2000 

-3000 

-4000 

-5000 

-6000 

-7000 

Zone B Zone E Zone A Zone D Zone C Zone F 

HTB2/WSA TRNSYS-TUD/TUD 

TRNSYS-16/ULg ESP-r/ESRU 

VA114-CirBm/VABI VA114-CirDf/VABI 

EnergyPlus/GARD VA114-CirBm-MZ355/VABI 

VA114-CirDf-MZ355/VABI EnergyPlus-MZ355/GARD 

Figure 9 In-depth diagnostic multi-zone delta 

sensible cooling loads (Neymark et al. 2008) 

CONCLUSIONS 

A number of important test method and software 

improvements were made as a result of this work: 

 The improved final agreement for shading cases 

using idealized/modeled calorimetry enabled us to 

identify disagreements and diagnose errors that 

may have been missed using the original IEA 

BESTEST shading cases (Judkoff and Neymark 

1995a). The level of disagreement in the original 

IEA BESTEST cases related to a number of 

simultaneous effects such as modeling realistic 

optical properties of glazing and interior opaque 

surfaces, along with realistic wall conduction and 

thermal mass. These simultaneous effects may 

have obscured disagreements caused by shading 

models. 

	 Of 49 disagreements found during the simulation 

trials, 31 were diagnosed and fixed, 11 were 

planned for investigation by the software authors, 3 

were judged as acceptable by the software authors, 

and 4 were awaiting notification of the software 

developer by the modeler. Several of the found 

errors affected some individual results by > 20%. 

A list of the problems found among the tested 

models, along with supporting details, are included 

in Part II of the final report (Neymark et al. 2008). 

Based on results after several iterations of 

BESTESTing, and resulting model improvements, all 

the tested programs now appear to have reliable 

models for phenomena isolated by the test cases 

including interzonal conduction, multi-zone shading, 

and internal windows where there are no multiple 

internal windows in series. These test cases did not 

address thermal inertia interactions for the modeled 

phenomena. Some remaining disagreements should 

be addressed, especially with respect to deficiencies 

identified for three of the models related to modeling 

a second internal window in series. The simulation 

results (with the noted exceptions) may therefore be 

useful as a reference or benchmark against which 

other software can be tested. 

With respect to the value of the test cases to software 

developers, a software-developer/vendor participant 

made the following comment about this IEA project: 

“Bestest and IEA-34/43 tests brought a number of 

new errors to the surface. This shows the importance 

of these test [cycles]!! And still there will be errors in 

the software!! Development of new, specific test 

cases is of big importance!!” (Wijsman 2008). 

Finally, the authors wish to acknowledge that the 

expertise available through the IEA and the 

dedication of the participants were essential to the 

success of this project. Over the four-year field trial 

effort, there were several revisions to the BESTEST 

specifications and subsequent re-executions of the 

computer simulations. This iterative process led to 

the refining of the new BESTEST cases, and the 

results of the tests helped us improve and debug the 

simulation models. The process underscores the 

leveraging of resources for the IEA countries 

participating in this project. Such extensive field 

trials, and resulting enhancements to the tests, were 

much more cost effective with the participation of the 

IEA-34/43 experts. 

Test Cases for Future Work 

This project developed a set of idealized in-depth 

diagnostic test cases for multi-zone conduction, 

multi-zone shading, and internal window models. 

During this project, participants discussed a number 

of important test case configurations that could not 

be included with the current test cases because of 

resource constraints. These test cases would include: 

 Shading case parametric variations, including: 

o Shading fin surface reflectance > 0 

Shaded Solar Radiation (kWh) 

5
 

 

 

 

 

 

 

 

 

 

 

 

o	 Modeling of multiple shading projections on a 

shaded area 

 Internal window parametric variations in a twozone context, including: 

o	 Two-zone version of Case MZ360 (idealized 

calorimeter) 

o	 Zero-conductance walls with realistic interior 

solar reflectance, with ideal windows 

o	 Realistic windows, with ideal walls (zeroconductance; interior solar absorptance = 1) 

o	 Realistic windows and zero-conductance walls 

with realistic interior solar absorptance 

o	 Realistic windows with realistic thermally 

conducting walls 

 Shading/internal window interaction. 

 Multi-zone shading and internal windows with 

thermal mass interactions. 

Additional cases to consider are described in Section 

2.5.3 of the final report (Neymark et al. 2008). 

ACKNOWLEDGEMENTS 

The work described in this report was a cooperative 

effort involving the members of the International 

Energy Agency (IEA) Testing and Validation of 

Building Energy Simulation Tools Experts Group. 

The group was composed of experts from the IEA 

Solar Heating and Cooling (SHC) Programme, 

Task 34, and Energy Conservation in Buildings and 

Community Systems (ECBCS) Programme Annex 

43. 

The project participants who provided most of the 

early simulation-trial work, preliminary sensitivity 

tests, and feedback on the test specification are listed 

as coauthors. We also gratefully acknowledge the 

contributions from modelers and authors of sections 

on additional computer programs used in this effort, 

including: 

 Robert Henninger and Michael Witte; GARD 

Analytics, United States: EnergyPlus 

 Julien L’Hoest, Christophe Adam, Philippe André 

and Corinne Rogiest; University of Liege, 

Belgium: TRNSYS-16 

 Harry Boyer, Frederic Miranville, and Alain 

Bastide; University of Reunion Island, France: 

CODYRUN 

 Bruno Peuportier; Paris School of Mines, France: 

COMFIE 

 Jean Noel; JNLOG, France: KoZiBu. 

We appreciate the support and guidance of Amir 

Roth, U.S. Department of Energy (DOE); Dru 

Crawley (now with Bentley Systems), former DOE 

representative to the IEA SHC Programme Executive 

Committee; and Richard Karney, DOE representative 

to the IEA ECBCS Programme Executive 

Committee. 

NOMENCLATURE (FOR RESULTS 

FIGURES) 

EnergyPlus/GARD: EnergyPlus run by GARD 

Analytics, U.S. 

ESP-r/ESRU: ESP-r run by Energy Systems 

Research Unit, University of Strathclyde, U.K. 

HIMASS,COOL: high mass, cooling 

HIMASS,HEAT: high mass, heating 

HTB2/WSA: HTB2 run by Welsh School of 

Architecture, Cardiff University, U.K. 

LOMASS,COOL: low mass, cooling 

LOMASS,HEAT: low mass, heating 

MZ340: six-zone, unshaded 

MZ350: six-zone, external shading device 

MZ355: seven-zone, building self-shading 

MZ360: three-zone, internal windows 

QA: cooling load for Zone A 

QB: cooling load for Zone B 

QB + QC: sum of cooling loads for Zones B and C 

Qbldg: cooling load for total building 

QC: cooling for Zone C 

TRNSYS-TUD: TRNSYS-TUD run by Dresden 

University of Technology, Germany 

TRNSYS-16/ULg: TRNSYS-16 run by University of 

Liege, Belgium 

VA114-CirBm/VABI: VA114 with circumsolar 

radiation modeled as beam radiation, run by VABI 

Software, The Netherlands 

VA114-CirDf/VABI: VA114 with circumsolar 

radiation modeled as diffuse radiation, run by VABI 

Software, The Netherlands 

630-620: difference between shaded and unshaded 

east/west window configurations, low mass 

construction 

930-920: difference between shaded and unshaded 

east/west window configurations, high mass 

construction 

REFERENCES 

ANSI/ASHRAE. 2007. ANSI/ASHRAE Standard 

140-2007, Standard Method of Test for the 

Evaluation of Building Energy Analysis 

Computer Programs. Atlanta, GA, USA: 

American Society of Heating, Refrigerating and 

Air-Conditioning Engineers. 

ANSI/ASHRAE. 2009. ANSI/ASHRAE Standard 

189.1-2009, Standard for the Design of HighPerformance Green Buildings. Atlanta, GA, 

USA: American Society of Heating, 

Refrigerating and Air-Conditioning Engineers. 

ANSI/ASHRAE/IESNA. 2007. ANSI/ASHRAE/ 

IESNA Standard 90.1-2007, Energy Standard 

for Buildings Except Low-Rise Residential 

Buildings. Atlanta, GA, USA: American Society 

6
 

 

 

 

 

 

 

 

 

 

 

 

 

 

of Heating, Refrigerating and Air-Conditioning 

Engineers. 

ASHRAE Handbook Fundamentals. 2009. Atlanta, 

GA, USA: American Society of Heating, 

Refrigerating and Air-Conditioning Engineers. 

CODYRUN. 2005. Saint-Denis, Reunion Island, 

France: University of Reunion Island. 

Eley, C. 2011. “COMNET Commercial Energy 

Services Network.” Presented at 2011 RESNET 

Building Performance Conference, Lake Buena 

Vista, FL, USA, February 28–March 2, 2011. 

EnergyPlus Version 2.1.0.012. 2008. Urbana, IL, 

USA: University of Illinois, and Berkeley, CA, 

USA: Lawrence Berkeley National Laboratory. 

ESP-r Version 11.5. 2008. Glasgow, Scotland, U.K.: 

Energy Systems Research Unit, University of 

Strathclyde. 

European Union. 2002. On the Energy Performance 

of Buildings. Directive 2002/91/EC of the 

European Parliament and of the Council, Official 

Journal of the European Communities, 

December. 

Haapala, T., Kalema, T., Kataja, S. 1995. Energy 

Analysis Tests for Commercial Buildings 

(Commercial Benchmarks). Report 101. Tampere, 

Finland: Tampere University of Technology. 

HTB2 Version 2.20AD. 2008. Cardiff, Wales, U.K.: 

Welsh School of Architecture, Cardiff 

University. 

Internal Revenue Service (IRS). 2008. Amplification 

of Notice 2006-52, Deduction for Energy 

Efficient Commercial Buildings. IRS Notice 

2008-40. Appears in Internal Revenue Bulletin 

(IRB) No. 2008-14, April 7, 2008. Washington, 

DC, USA: U.S. Department of Treasury, Internal 

Revenue Service. 

Judkoff, R. 1988. “Validation of Building Energy 

Analysis Simulation Programs at the Solar 

Energy Research Institute.” Energy and 

Buildings, 10(3):235. Lausanne, Switzerland: 

Elsevier Sequoia. 

Judkoff, R., Neymark, J. 1995a. International Energy 

Agency Building Energy Simulation Test (IEA 

BESTEST) and Diagnostic Method, NREL/TP472-6231. Golden, CO, USA: National 

Renewable Energy Laboratory. 

www.nrel.gov/docs/legosti/old/6231.pdf. 

Judkoff, R., Neymark, J. 1995b. Home Energy Rating 

System Building Energy Simulation Test (HERS 

BESTEST). NREL/TP-472-7332a and TP-472­

7332b. Golden, CO, USA: National Renewable 

Energy Laboratory. 

www.nrel.gov/docs/legosti/fy96/7332a.pdf. 

Judkoff, R., Neymark, J. 2006. “Model Validation 

and Testing: The Methodological Foundation of 

ASHRAE Standard 140.” ASHRAE Transactions 

112(2):367–376. Atlanta, GA, USA: American 

Society of Heating, Refrigerating and AirConditioning Engineers. 

Judkoff, R., Neymark, J. 2009. “What Did They Do 

in IEA 34/43? Or How to Diagnose and Repair 

Bugs in 500,000 Lines of Code.” Proceedings of 

Building Simulation 2009. July 27–30, Glasgow, 

Scotland. International Building Performance 

Simulation Association. 

Judkoff, R., Wortman, D., O’Doherty, B. Burch, J. 

2008. A Methodology for Validating Building 

Energy Analysis Simulations. NREL/TP-550­

42059. Golden, CO, USA: National Renewable 

Energy Laboratory. Based on unpublished report 

of 1983 with same authors and title, previously 

referenced as SERI/TR-254-1508. 

KoZiBu. 2005. Villeurbanne, France: INSA de Lyon; 

Lyon, France: JNLOG. 

Neymark, J., Judkoff, R. 1997. “A Comparative 

Validation Based Certification Test for Home 

Energy Rating System Software.” Proc. Building 

Simulation ’97. September 8–10, Prague, Czech 

Republic. International Building Performance 

Simulation Association. 

Neymark, J., Judkoff, R., Alexander, D., Felsmann, 

C., Strachan, P., Wijsman, A. 2008. 

International Energy Agency Building Energy 

Simulation Test and Diagnostic Method (IEA 

BESTEST) Multi-Zone Non-Airflow In-Depth 

Diagnostic Cases: MZ320 -- MZ360. NREL/TP550-43827. Golden, CO, USA: National 

Renewable Energy Laboratory. 

www.nrel.gov/docs/fy08osti/43827.pdf. 

Peuportier, B.. Sommereaux, I. 1994. COMFIE 

Users Manual. Paris, France: Paris School of 

Mines. 

RESNET. 2006. Mortgage Industry National Home 

Energy Rating Systems Standards. Oceanside, 

CA, USA: Residential Energy Services Network, 

Inc. 

www.resnet.us/standards/RESNET_Mortgage_I 

ndustry_National_HERS_Standards.pdf. 

RESNET. 2007. Procedures for Verification of 

International Energy Conservation Code 

Performance Path Calculation Tools. RESNET 

Publication No. 07-003. Oceanside, CA, USA: 

Residential Energy Services Network, Inc. 

www1.resnet.us/standards/iecc/procedures.pdf. 

TRNSYS-TUD. 2008. Dresden, Germany: Dresden 

University of Technology. 

TRNSYS-16 Version 16.00.0037. 2005. Madison, WI, 

USA: Solar Energy Laboratory, University of 

Wisconsin. 

VA114 Version 2.25. 2008. Delft, The Netherlands: 

VABI Software BV. 

7
Wijsman, A. 2008. Modeler Report for BESTEST 

Cases MZ320-MZ360, VA114 Version 2.25. 

Delft, Netherlands: VABI Software BV. 

Included with Section 2.9, Appendix II-F, of 

Neymark et al. (2008). 

8