Conference Paper

NREL/CP-550-47522

August 2010

On the Use of Integrated 

Daylighting and Energy 

Simulations To Drive the 

Design of a Large Net-Zero 

Energy Office Building 

Preprint 

Rob Guglielmetti, Shanti Pless, and 

Paul Torcellini

Presented at SimBuild 2010

New York, New York

August 15–19, 2010
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ON THE USE OF INTEGRATED DAYLIGHTING AND ENERGY SIMULATIONS TO 

DRIVE THE DESIGN OF A LARGE NET-ZERO ENERGY OFFICE BUILDING

Rob Guglielmetti, Shanti Pless, and Paul A. Torcellini, Ph.D. P.E. 

National Renewable Energy Laboratory, Golden, CO USA 

This paper seeks to illustrate the challenges of 

integrating rigorous daylight and electric lighting 

simulation data with whole-building energy models, 

and defends the need for such integration in order to 

achieve aggressive energy savings in building designs. 

Through a case study example, we examine the ways 

daylighting – and daylighting simulation – drove the 

design of a large net-zero energy project.

ABSTRACT

In this paper, the author will give a detailed review of 

the daylighting and electric lighting design process for 

the National Renewable Energy Laboratory’s Research 

Support Facility (RSF)1

, a 220,000 ft2 net-zero energy 

project the author worked on as a daylighting 

consultant. A review of the issues involved in 

simulating and validating the daylighting performance 

of the RSF will be detailed, including daylighting 

simulation, electric lighting control response, and 

integration of Radiance simulation data into the 

building energy model. Daylighting was a key strategy 

in reaching the contractual energy use goals for the 

RSF project; the building’s program, layout, 

orientation and interior/furniture design were all 

influenced by the daylighting design, and simulation 

was critical in ensuring these many design components 

worked together in an integrated fashion, and would 

perform as required to meet a very aggressive energy

performance goal, as expressed in a target energy use 

intensity (EUI). 

The urgency of increasing energy efficiency in new 

building design and retrofits (and the need to 

demonstrate the effectiveness of lighting efficiency 

measures for code compliance and sustainable building 

ratings) has moved lighting simulation into a central 

role in sustainable lighting design. At the same time, 

energy modeling – long an established paradigm for 

INTRODUCTION

 

1 http://www.nrel.gov/sustainable_nrel/rsf.html

evaluating the whole-building energy use of a given 

design – has also become an essential component of 

any code-compliant or sustainably rated building 

design process. 

A fundamental aspect to any optimized sustainable 

building design is the integration of many disparate 

building components so that they efficiently function 

as a single entity, but many of a building’s systems are 

sized, designed and specified through individualized 

system-specific tools or code tables. Lighting designs 

are evaluated for how well they meet a target 

illumination level, chillers are sized to meet a certain 

cooling load, etc. But the potential exists for the 

lighting and the cooling systems to work in concert 

with one another through intelligent control of the 

lighting in response to available daylight, reducing 

both cooling and lighting loads, for example. Windows 

can allow natural daylight into a space, but they also 

can hasten heat losses in winter due to the decreased 

insulating capability of even advanced window glazing 

compared to traditional wall constructions. An optimal 

architectural design responds to all the variables that 

affect the various building systems, and the building 

itself. This optimization is most efficiently discovered 

through simulation.

Software tools exist today that can perform rigorous 

analysis of extremely complex physical interactions

within buildings: lighting simulation, HVAC 

simulation, and computational fluid dynamics (CFD) 

tools are available to simulate many of these building 

elements, and they have each been developed to look 

at their respective pieces in great detail. But 

historically, the results of these simulations could not 

easily be shared from one modeling paradigm to 

another. Worse, modeling these different systems 

independently of one another flies in the face of 

integrated design. While the argument for integration 

is strong, some significant barriers remain:

1
• Energy analysis tools such as EnergyPlus2 and 

DOE-23 incorporate a daylighting function, 

however the algorithms employed to derive 

interior space daylight levels are crude 

compared to the more robust algorithms used 

in more specialized lighting simulation and 

analysis tools such as Radiance4

 (hybrid 

Monte Carlo and deterministic ray tracing 

approach) and AGi325

• Even relatively simple daylighting-oriented 

building designs that result in a concave 

building section cannot be simulated in 

EnergyPlus or DOE-2 due to limitations in the 

software. 

(radiosity). 

• Typical building models created for a building 

energy simulation will have infinitely thin wall 

constructions and other geometric 

simplifications in the model that 

mischaracterize the true relationship of the 

building form (and, critically, the electric 

lighting and photosensors) to the available 

daylight. 

• A number of new daylighting strategies rely 

on advanced methods for delivering and 

redirecting daylight into spaces to improve the 

performance of a daylighting design. These 

so-called complex fenestration systems (CFS) 

offer the promise of delivering glare-free 

daylight to spaces for greater periods of the 

year, and to spaces that otherwise would never 

receive daylight, such as core spaces far from 

the building perimeter. The challenge of 

simulating the performance of CFS remains 

significant, however, particularly in an annual 

(hourly) simulation modality, even when 

advanced lighting simulation tools such as 

Radiance are used.

Perhaps as a result of these differences in modeling 

approaches and capabilities, energy- and daylightmodeling simulation tools have evolved on parallel but

separate paths. There exist tools on both sides of the 

challenge to arrive at simulation-based performance 

evaluations of a given design, and the industry has 

used these tools very much in this parallel manner, 

largely relying on experience and intuition to integrate 

 

2 http://apps1.eere.energy.gov/buildings/energyplus/

3 http://doe2.com/DOE2/index.html

4 http://radsite.lbl.gov/radiance/HOME.html

5 http://www.agi32.com

the results from these two separate analytical exercises. 

Certainly each simulation can inform the other, and if 

the daylighting design is simple enough – e.g. relies on 

windows and not CFS and occupant behavior 

modeling is not critical – then the methods within 

DOE-2 or EnergyPlus are adequate for determining the 

performance of a given design, and the more rigorous 

methods employed by Radiance or AGi32 can be used 

for demonstrating code and design guideline 

compliance (e.g. illuminance levels) and for 

visualizations and other analysis such as glare or 

photocontrol studies. It could be said that this is de 

rigueur in current sustainable building design. Indeed, 

the author has operated in this fashion for years, 

successfully. It took a unique project, with a very strict 

energy-use intensity goal, to take a different tack.

A number of dedicated lighting simulation software 

tools exist such as Radiance [Ward 1994], AGi32,

Autodesk 3ds Max Design, Dialux, Relux, et al. that 

give researchers and designers the ability to evaluate 

complex lighting designs, within complex architectural 

spaces. These programs are capable of simulating the 

performance of electric lighting fixtures (assuming a 

photometric information file based on a physical 

luminaire test report is provided), as well as the 

contributions from the sun and sky hemisphere, as well 

as ground reflections and the effects of local 

obstructions. These programs generally employ a 

radiosity or light-backwards raytracing algorithm to 

derive the photometric quantities of illuminance or 

luminance needed for the lighting design evaluation. 

Some of these programs have been independently 

validated [Mardaljevic 2000, Reinhart C F, Breton P-F 

2009] and a trained user of these tools can expect 

accurate, physically-based simulation results.

Depending on the program, a number of phenomena 

critical to the valid evaluation of the lighting 

performance can be simulated: transmittance and 

reflection (both diffuse and specular), absorption, 

chromatic effects, and of course the luminous flux 

distribution of both electric luminaires and daylight 

(sun and skylight as defined by a variety of sky models 

[ISO/CIE 2003, Perez 1993, Preetham 1999]). These 

tools all present the simulationist with more advanced 

lighting simulation capability over the daylighting 

tools found within popular building energy simulation 

tools such as EnergyPlus or DOE-2. 

CURRENT LIGHTING SIMULATION 

TOOLS

Arguably the most flexible of all the lighting 

simulation tools is Radiance. This open source 

software is built upon the unix toolbox model. 

Unconstrained by a graphical user interface (though 

2
some commercial and open source GUIs do exist), 

Radiance is a collection of programs that can be strung 

together via complex command line pipelines, shell 

scripts, or other glue programs such as Ruby, Python 

or Perl, to perform a variety of lighting simulation 

tasks. In addition to providing what is possibly the 

most rigorous lighting simulation capability currently 

available, Radiance has been extensively validated and 

is actively supported by its developer and the general 

Radiance user community6

At their most basic modality, these tools operate on a 

single point-in-time basis; that is, they are all designed 

to arrive at a solution for a given set of conditions, 

such as site latitude and longitude, building orientation,

time of day, day of year, and sky condition. While the 

electric lighting can generally be simulated in a single 

calculation, a full understanding of the daylight 

contribution to a building’s overall lighting design 

cannot be gleaned from a single simulation of a single 

point in time or sky condition. For an annual 

simulation, most of these programs employ some type 

of automated “daylight study” function, that 

automatically increments the time of day by some 

value to get a set of results that give an overview of the 

daylight and electric lighting performance over the 

course of the year. In these cases, the annual dataset is 

the end result of running a lengthy calculation, 

multiple times. Depending on the complexity of the 

simulation (number of light sources, building geometry 

detail), each point in time calculation can take several 

minutes to several hours; as a result, annual 

simulations rarely have the hourly resolution that is de 

rigueur in a typical energy modeling simulation in

DOE-2 or EnergyPlus. 

. Perhaps owing to all of 

these features, Radiance also serves as the background 

“engine” performing the actual lighting calculations 

for a number of other lighting software tools such as 

SPOT, Daysim, and indirectly, Ecotect.

Common practice to keep these simulations tractable is 

to reduce the resolution of an annual simulation from 

monthly to seasonal. In this case, several “key days” 

are simulated, such as the equinox and the solstices, on 

an hourly – or more typically, semi-hourly – basis. 

This gives a range of illuminance levels resulting from 

extreme sun angles (low and high), and a midrange 

number as a result of the equinox simulation. From 

there, interpolation or intuition is used to understand 

the remainder of the annual distribution. In other 

words, experience and intuition tend to serve as data 

proxies, in order to expand a coarse dataset into a finer 

one due to simulation time constraints. The 

 

6 http://www.radiance-online.org

simulationist is left with a dataset that contains data 

from multiple estimations, of variable rigor.

Another approach involves the use of daylight 

coefficients [Tregenza and Waters 

1983; Mardaljevic 2000, 2000; Reinhart 2001, 

Reinhart and Walkenhorst 2001]. With this approach, 

the contribution of light at a point is solved for many 

discrete sky segments and sun positions and then these 

coefficients are applied to a weather file through 

simple matrix multiplication. The initial calculation of 

the daylight coefficients is lengthy, but the hourly 

timestep illuminance calculations are very fast, 

allowing for annual illuminance estimations at the 

resolution typical for energy simulations (hourly) in a 

more reasonable timeframe. This approach has been 

used in research circles for several years, and is also 

the basis for the simulations in Daysim. Daysim is the 

only “packaged” software that offers the lighting 

simulationist the ability to analyze a daylighting design 

with daylight coefficients. To date, all daylight 

coefficient-based simulation approaches employ 

Radiance at the core. 

One limitation that all of these tools exhibit is the 

inability to accurately solve for high flux light 

transport through so-called daylight redirection devices 

that employ specular optical redirecting surfaces. Light 

pipes, tubular daylight devices (TDDs), daylight 

redirecting devices and other CFS are generally best 

simulated with a forward raytracer (TracePro, 

Photopia. et al.), and the resulting performance 

mapped to a luminous descriptor. The standard format 

for this in lighting simulation software is the IESNA 

LM-63 Standard Format for the Transfer of 

Photometric Data – the same format used for tested 

luminaires. This method in essence concentrates the 

luminous flux from the sun and sky and all the optical 

redirections caused by the CFS onto a point (which is 

then usually spread over an area) just inside the CFS, 

allowing it to be treated as a direct light source in the 

lighting simulation. While this method works well, it 

requires a forward raytrace simulation for every 

timestep needed in the annual simulation or daylight 

study because the sun – the most significant 

contributor to the solution – is changing position at 

every timestep. Discrete simulations are also required 

for every site location (latitude & longitude), façade 

orientation, and for any significant obstruction 

conditions. As a result, the use of daylight redirecting 

technologies – potentially significant contributors to 

the viability of any daylighting design – is at this time 

very difficult to integrate into an annual simulation. 

The current research work in this area is discussed 

further in a following section (see “Future Trends”). 

3
The National Renewable Energy Laboratory’s 

Research Support Facility (RSF) is the newest building 

on NREL’s campus, slated for completion in June of 

2010, and was designed from the outset to be a netzero energy building (NZEB). Indeed, the entire 

procurement process was designed to result in a 

building that produces as much energy as it consumes, 

on an annual basis. 

CASE STUDY:

With any NZEB, energy efficiency is a top priority. As 

such, the original RFP for the RSF included an annual 

energy use intensity (EUI) goal of 25 kBtu/ft2. This 

requirement was based on standard government 

building occupant density of 650 employees, 220,000 

ft2

, and a data center to service the RSF occupants. 

Design efficiencies in space planning increased the 

number of potential occupants to 822 in the same floor 

area, and increased the number of people being served 

by the data center to approximately 1,200. With these 

increases in employee density, space efficiency, and 

data center loading, the RFP allowed for a per-person 

EUI goal normalization. The required EUI has thus 

been normalized to 32 kBtu/ft2 with the prorated data 

center for 822 occupants, or 35 kBtu/ft

2 with the full 

data center loading. On-site renewable energy sources 

(PV and a wood chip furnace) will provide onsite 

power and supplemental heating, toward the ultimate 

goal of achieving a net-zero energy building (and an 

energy consumption rate at least 50% below ASHRAE 

Standard 90.1-2004). The RSF will also attain a 

NZEB:B-classification, meaning that all renewable 

energy sources needed to offset the building’s energy 

use are located within the building site [Crawley, et al. 

2009]. In addition to the EUI target, LEED Platinum 

certification by the United States Green Building 

Council (USGBC) was a project requirement, in 

particular the LEED Indoor Environmental Quality 

Part 8.1 (Daylight) credit.

Verification of the building’s energy performance was 

needed, at an early stage in the design, in order for the 

design-build team to proceed in confidence. 

Given the aggressive EUI goal, and the fact that the 

LEED daylight credit was an RFP mandate, 

daylighting was one energy efficiency strategy 

considered an essential component of the overall 

building design. Work to integrate and best take 

advantage of daylighting for this project took place 

during the design competition phase. It was in this 

conceptual phase that daylighting simulation with 

Radiance was already being used. After some basic 

best practices were employed (e.g. creating a long 

building plan form with the long axis aligned east-west 

for optimal daylight access and controllability, open 

space planning, and the creation of a high-mounted 

“daylight glazing” and a lower, shielded, “vision 

glazing” fenestration style), the team sought to extend 

the south daylight-illuminated zone as far north as 

possible, in plan. A daylight redirection device called 

the LightLouver Daylight System was selected to 

occupy the daylight glazing to provide glare control as 

well as to redirect the incoming solar radiation onto the 

ceiling and deeper into the space. In order to explore 

the capability of the LightLouver to maximize the floor 

depth, a 3D building model of the typical office wing 

was created in AutoCAD and simulated in Radiance. 

With an eye toward the LEED iEQ8.1 goal, point-intime simulations were conducted using Radiance to 

determine how broadly an illuminance level of 25 

footcandles could be achieved at 30” above the 

finished floor under clear skies, at noon, on the 

equinox – one of the compliance demonstration 

methods available under LEED iEQ 8.17

Extensive modeling by the design competition team 

revealed 60’-0” to be the maximum floor plan depth 

(north-south) that could be illuminated to the criteria 

set forth by the LEED compliance standards (i.e. 75% 

of normally occupied space achieving 25 footcandles 

under a clear sky at noon on the equinox). The 

Radiance model was modified to study different 

fenestration options such as window head heights, 

window to wall area ratios, glazing transmittance; 

different interior finishes were studied (mainly for the 

effect different surface reflectances had on 

illumination); furniture options such as partition height 

and interior wall and ceiling configurations were also 

investigated. With the preliminary selections on 

fenestration, glazing transmittance, and ceiling height, 

extending the floor depth north-south beyond 60’-0” 

created too large of a dark area approximately 2/3 

north of the south perimeter that did not receive 

adequate daylight to allow for cost-effective dimming 

or switching of the electric lights (i.e., < 25 

footcandles), and this essentially fixed the north-south 

dimension of the main office space wings of the 

building design at 60’-0”. This was one of the first 

areas of the building design that was directly affected 

. A 

photometric file in the IESNA LM-63 format, 

representing the luminous output of a LightLouver unit 

located near the project site, under clear skies, at noon, 

was supplied by the manufacturer. This allowed for an 

efficient, accurate evaluation of the potentially 

significant contribution of the daylight-redirecting 

units for that timestep. 

 

7 This project is being certified under LEED v2.2; the 

new LEED 3.0 simulation-based compliance path for 

the daylight credit is slightly different.

4
and shaped through daylight simulation. Interestingly, 

the integrated design of all these elements was being 

studied and simulated at a high degree of detail as far 

back as the design competition phase, even before the 

project was awarded to a design-build team. 

Once the project was awarded and advanced to the 

design development phase, the author became involved 

in the project. As the project progressed through this 

phase, changes crept into the design, and previous 

estimates regarding room finishes and furniture 

dimensions had become more firmly established. As a 

result an entirely new building model was created, 

reflecting the known design to date for the main office 

wing area. The previous evaluation calculation 

(equinox design day) was re-done, and at that time it 

was discovered that the LEED criteria was no longer 

being met for the required 75% of the floor area. Initial 

results from Radiance simulation showed 69% of the 

floor area receiving at least 25 footcandles. Because 

the main office wings represent the majority of 

occupied space on the project, this model needed to 

show at a minimum that a 25 fc illuminance level was 

being maintained for LEED compliance. 

While not pleasant news to break to the design team, 

the simulations allowed this news to be broken early, 

at a time when changes were cheaper and easier to 

integrate. 

Once again, Radiance was used to evaluate various 

changes to the design to evaluate their impact on the 

daylighting, and a series of changes were 

recommended. Changes included increasing the size 

and lowering the mounting height of the LightLouver 

units, and a fortuitous discovery that the acoustical 

ceiling panels being installed to the metal decking had 

a surface reflectance higher than the white paint that 

was used in the initial simulation. 

These changes were incorporated into the Radiance 

model, and by this time the model had been fairly well 

refined to represent the actual building design. The 

updated Radiance simulations showed that the main 

office wings were well-saturated with daylight, 

particularly the top floor, which has a sloped ceiling to 

optimize the orientation and hence the efficiency of the 

photovoltaic panels on the roof. Initially there was 

concern that the sloped roof would create a problem 

for the daylight redirection devices, by moving the 

reflecting surface up and away from the redirected 

sunlight. In fact, the Radiance simulations indicated 

that the roof slope actually improved the daylight 

uniformity on the top floor workplane, because the 

illuminance peak on the ceiling was moved farther 

back (farther north, in plan) on the ceiling, thus 

providing more redirected light to the northern half of 

the floor plate. At the same time, the roof slope 

decreased the incident angle of the sunlight on the 

ceiling, reducing the reflected daylight quantity at the 

perimeter where there was already an abundance of 

daylight. The overall effect was to increase the 

uniformity of the daylight illumination on the work 

plane on the top floor, essentially redistributing the 

wealth of daylight at the south perimeter more 

equitably to the entire floor plate. Figure 1 graphs the 

task illuminance profiles for the top and typical office 

wing floors on the equinox from north to south (left to 

right), while Figure 2 and Figure 3 show renderings of 

the top and typical floors, respectively. As Figure 1

illustrates, the top floor’s sloped ceiling reduces the 

illuminance peak at the south perimeter, and the 

illuminance levels further north are increased, 

providing 50 to 60 footcandles across the entire top 

floor task plane. 

Top Floor Vs. Typical Floor

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Calculation Point

Illuminance (fc)

Typical Floor

Top Floor

Figure 1: Task Illuminance Comparison, Top Versus 

Main Floors

Figure 2: Radiance Rendering of Top Floor

Figure 3: Radiance Rendering of Typical Floor

5
The next area of focus was the optimization of the 

electric lighting control zones such that they are best 

able to respond to available daylight while not being 

overly subdivided, which would have added cost and 

complexity to the design. For this, the Radmap8 utility 

was used to generate annual illuminance plots of each 

floor of the RSF. Radmap is a Python script that parses 

a typical meterological year (TMY) weather file and 

generates a “cumulative sky” description for use in 

Radiance9

As the main goal of this portion of analysis was to 

optimally group the electric light fixtures into zones 

that would be controlled during normal business hours, 

the TMY weather file was modified to include only the 

hours between 7:00 a.m. and 6:00 p.m. The resulting 

cumulative sky produced by radmap therefore 

described the daylight behavior we were most 

interested in. 

. The cumulative sky is simply an amalgam 

of all the daytime skies for a given climate, as defined 

by the direct normal and diffuse horizontal irradiance 

in the TMY file, translated to Radiance “gensky” 

commands, and thus to CIE standard sky types. The 

cumulative sky therefore contains several thousand 

solar light source descriptions, as well as a summed 

luminous distribution for all of the hourly sky and 

ground hemispheres. This file can then be combined 

with a Radiance building model and from this a single 

Radiance simulation will yield a cumulative radiative 

quantity, and, more importantly for this exercise, 

interior distribution. 

The task of simulating the performance of the 

LightLouver units under such a sky model was the 

next consideration. As mentioned in the preceding 

section, CFS devices generally require a forward 

raytrace evaluation in order to accurately capture the 

contribution of the sun and sky through the CFS. The 

design team was unable to obtain a photometric file for 

a LightLouver unit under the hypothetical cumulative 

sky produced by radmap, so the model was updated to 

include the actual LightLouver geometry itself, and the 

light backwards ray tracing algorithm of Radiance was 

relied upon for locating all the direct sun and sky 

contributions. The LightLouver manufacturer was able 

to provide the design team with an actual 2D shop 

drawing of the LightLouver units in AutoCAD format, 

and the section was extruded into 3D geometry and 

placed in the Radiance model. Considering the odds of 

 

8 http://www.dream.unipa.it/dream/pub/dot/anselmo

/radiance/05.php

9 There are multiple sky generation options to radmap, 

but the cumulative sky option was the most useful for 

this exercise.

a ray making the journey from the camera plane, into 

the space, through the LightLouver slats and out into 

the sky dome to intersect a sun disc subtending one 

half of a degree, even with fairly aggressive simulation 

parameters, the expectation was that some solar flux 

would not be accounted for. This was an admittedly 

conservative approach to estimating the total 

illumination on the work plane, but one the team was 

comfortable with, and one that was tractable given the 

design schedule. 

A parallel plan projection view of each floor was 

rendered with the Radiance rpict program; given the 

large number of solar light sources – and the 

aggressive settings required to ensure the light sources 

were accounted for as best as possible – the 

simulations took several hours to complete for each 

floor. But when visualized in falsecolor, the renderings 

afforded a clear view of the resulting daylight 

distribution in the space and allowed the design team 

to logically circuit the electric light fixtures so that 

they could best respond to the daylight while not 

adding too many zones. The distribution across the 

core was fairly uniform, leading to the decision to zone 

the two core rows of light fixtures together, rather than 

separately. The remaining rows were circuited into 

their own zones – a north perimeter zone and a south 

perimeter zone. It was also determined that the 

daylight saturation at the south perimeter was so high 

that the added resolution of continuous dimming 

ballasts was not needed, and lower-cost switching 

ballasts were used for this zone instead.

Figure 4: Cumulative Annual Sky Falsecolor 

Rendering

At this point in the design process, Radiance 

simulations helped to refine the building plan, 

fenestration, surface finishes, glazing transmittances, 

furniture dimensions and orientations, and lighting 

dimming zones. Radiance would now be called upon to 

provide a link to the energy model so the engineers 

doing the energy modeling – and ultimately 

responsible for determining the building’s final EUI – 

had an estimate of the hourly lighting system response 

6
to the available daylight, one that incorporated the 

CFS. However conservatively this estimate was (given 

the process), this was better than not taking it into 

account at all (which was the only option available to 

the engineers modeling building energy use in DOE-2, 

since DOE-2’s daylight simulation models cannot 

incorporate CFS).

For this phase of analysis, the Sensor Placement and 

Optimization Tool, or SPOT10

It was this capability of SPOT to predict the dimming 

response that led the author to use SPOT for the annual 

simulations of the RSF project. By default, SPOT is 

limited to the creation of simple box-type spaces by the 

user interface, but the author worked with a member of 

the SPOT development team who was able to use 

SPOT to analyze the daylighting controls on our 

detailed RSF model directly. Photometric files for the 

electric lights were obtained from the lighting 

designer; the exact luminaire layouts were added to the 

Radiance model, and were circuited and controlled as

per the recommendations that came out of the 

preceding daylight simulations with the cumulative 

annual sky.

, was used. A feature of 

SPOT is the ability to generate a lighting schedule that 

can be merged with the DOE-2 energy simulation as a 

so-called “include file”. This allows one to utilize 

Radiance for a rigorous evaluation of the direct and 

global illumination, using a validated light-backwards 

raytracing algorithm, and then to evaluate – using 

rsensor, a new tool added to the Radiance toolbox – a 

given photosensor’s spatial response to the available 

daylight and resultant dimming or switching response 

over a number of control algorithms. This produces an 

8,760-hour schedule of the lighting power fraction for 

a given design, in a given climate. While still divorced 

from the building energy use simulation, this 

represents a significant improvement in the depth and 

rigor of the lighting simulation portion of an annual 

energy simulation, and the ability to export the electric 

lighting system’s control response to DOE-2 (and 

EnergyPlus with minor reformatting) poses a 

significant improvement in the integrated simulation 

and estimation of building energy savings through 

daylighting measures. 

SPOT uses Radiance “behind the scenes” to generate a 

set of seasonal daylight illuminance data, based on CIE 

standard sky types (clear and overcast) to establish an 

idealized baseline of daylight saturation potential. 

From there the user can interactively investigate the 

effect of changing setpoints, bandwidth, and control 

 

10 http://www.archenergy.com/SPOT

algorithms to arrive at an optimal control scheme for 

the lighting design.

A TMY weather file is then provided to the program, 

and the file is parsed for sky conditions. The global 

horizontal daylight illuminance values computed in the 

first pass using CIE skies are then weighted by the 

values found in the TMY weather file, thus deriving a 

more climate-specific estimate of available daylight. 

This is accomplished in the following way: 

illuminance data in the TMY file, specifically, diffuse 

horizontal divided by global horizontal illuminance, is 

used to determine a sky cover ratio. The sky cover 

ratio along with solar declination are used to 

interpolate the daylight factors that were previously 

determined using a CIE sky and calculated global 

horizontal illuminance. Then, global horizontal 

illuminance data from the TMY file is used to scale the 

interpolated daylight factors into workplane 

illuminance. The resulting control response is 

computed using rsensor. As rsensor can accept spatial 

photosensor sensitivity data, which is available for a 

number of commercial photosensor models11

At this point SPOT can generate an 8,760-hour 

schedule of the lighting power fraction for up to three 

lighting control zones in a space. This schedule can 

then be exported and saved in the standard DOE-2 

include file format.

, this 

provides yet another level of depth to the daylighting 

simulation.

This simulation was carried out for each floor of the 

RSF and the include files were then passed to the 

mechanical engineers on the project and used in the 

building energy simulations in lieu of the internal split 

flux daylighting calculation that DOE-2 utilizes. 

Several coordination exercises were undertaken 

between the author and the mechanical engineers to 

ensure that building envelope, lighting layouts, lighting 

power densities, control zones and occupancy 

schedules were in alignment between the two models. 

Currently, the RSF project is under construction and is 

scheduled for completion in the summer of 2010. The 

current energy analysis – conducted with DOE-2 and 

incorporating the Radiance/SPOT-based daylighting 

simulation – predicts the RSF will use 3% less energy 

than the normalized 35 kBtu/ft2

/yr EUI goal, and 

projects energy use from lighting at 11%, 

approximately 7% below the national average. Should 

the building perform as expected, the RSF will be one 

 

11

http://www.lrc.rpi.edu/nlpip/publicationDetails.asp?id

=916&type=1

7
of the largest net-zero energy buildings in the world. 

The building will be extensively monitored postoccupancy and we expect the lighting energy use to be 

even lower than the simulation predictions, since the 

LightLouver contributions were very conservatively 

estimated in simulation. The realized building 

performance will certainly be the topic of a future 

paper(s). 

For a project with such aggressive energy use goals, all 

disciplines needed to contribute to the overall 

reduction in energy use, and simulation of a fine 

resolution was required in order for every measure to 

be accounted for. Traditional pathways to energy 

efficiency in the lighting design were pushed to 

include new technologies that resisted simulation 

efforts, and in the end the Radiance toolset was applied 

in a variety of ways to satisfy the project’s simulation 

and verification needs. The parallel path of Radianceand DOE-2-based simulation required careful 

coordination between disciplines, as well as two 

building models. While not a perfect solution, this 

method did allow for a much more detailed analysis of 

the daylighting and electric lighting response to the 

available daylight. This also placed the responsibility 

of properly defining the electric lighting and control 

systems in the hands of the lighting and daylighting 

engineers, and allowed the mechanical engineers to 

focus on the specification of the remainder of the 

building systems. We believe this approach ensures the 

lighting simulations, as part of a whole building energy 

simulation, are as representative as possible and 

improves overall simulation quality. 

As this paper was being finalized, construction of the 

RSF was nearing completion, and the author had an 

opportunity to match a low dynamic range photograph 

of the main office space with a Radiance rendering. 

The initial results are shown in 

VALIDATION

Figure 5 and Figure 6. 

We believe these images clearly illustrate the power of 

simulation in a qualitative context. Upon occupancy,

high dynamic range (HDR) images will be taken of the 

RSF; these will likely match even better, visually, as 

Radiance renderings are high dynamic range images in 

their own right and therefore we can tonemap the two 

HDR images with the same global operator. 

A potential future research project involves comparing 

simulation and HDR images of the RSF with user 

feedback solicited over the course of the coming year, 

to attempt to develop methods for using images to 

predict and identify “good” (and “bad”) lighting. The 

RSF will also be closely monitored for energy use and 

illuminance levels for a period of one year following 

owner turnover in June of 2010, and during that time 

we expect to gain some additional insight about 

simulation’s quantitative predictive capability.

Figure 5: RSF Construction Photo

Figure 6: RSF Radiance Rendering

As mentioned, Radiance employs a light-backwards 

ray tracing algorithm; one area where this algorithm 

comes to difficulty is when very small, very high flux 

light sources are obscured and/or redirected by 

geometry. The traditional methodology for resolving 

this is to use Radiance’s mkillum utility to essentially 

move the initial light backwards ray origin from the 

view or calculation point to a point as close to the CFS 

as possible, conduct a standard Radiance raytracing 

exercise from there, and gather that data and use that as 

the basis for a direct light source in the subsequent 

Radiance simulation. The best method is to use a 

forward raytracer (TracePro et al.), or to physically test 

a sample of the CFS, and map the resulting 

performance to a luminous descriptor. While these 

methods work well, they require lengthy simulations or 

testing for every timestep, orientation and sky 

condition that would appear in the annual simulation or 

daylight study – an intractable problem. 

FUTURE TRENDS:

8
A new proposal for solving a CFS distribution on an 

annual basis is the so-called “three-phase method” 

[Ward 2007]. New tools (rtcontrib, genklemsamp, 

genskyvec, dctimestep) have been added to Radiance

in version 4.x that will potentially enable the lighting 

simulationist to create bidirectional scattering

distribution functions (BSDFs) for CFS materials, and 

to apply them in a daylight coefficient-based annual 

daylight simulation. 

This work is ongoing and is of great interest to those in 

the daylight simulation community, as it represents a 

pathway toward producing truly dynamic, climatebased daylight simulations that potentially can include 

contributions of CFS, occupant behavior models, 

granular control of electric lighting and photosensor 

control. 

Bourgeois et al. (2008) also propose a refinement of 

the daylight coefficient / Daysim approach as well as a 

data format that could be used for sharing of daylight 

simulation data with building energy models. This 

proposed DDS standard daylight coefficient model

increases the resolution of the daylight coefficient sky 

discretization scheme, is potentially rotationally 

invariant, includes dynamic shading elements in an 

annual daylight simulation, and defines a standard 

XML file format to structure the daylight coefficient 

data and calculated daylight performance metrics on a 

sensor point basis. 

Emerging Radiance tools released in Radiance version 

4.x that serve and work with data computed by 

rtcontrib, along with the DDS standard daylight 

coefficient model, form the foundation of a potentially 

large leap in the capability of the daylighting 

simulationist. The mathematical rigor of the 

calculations, the potential for hourly resolution of time 

series data (computable in reasonable timeframes), the 

ability to evaluate dynamic responses to daylight 

availability (via lighting controls, electrochromic 

glazing, occupant control of blinds & shades, etc.), and 

the standard format proposed for organizing the wealth 

of data these simulations can generate – and for 

sharing it all with energy models, design teams, 

utilities, building information models (BIMs) and 

building rating systems – represents a significant 

change in the way daylight simulation will factor into 

the design and construction process. Codes, standards 

and building rating systems will continue to evolve, in 

some cases adopting these tools and methods as their 

agents of formulation and refinement, and for 

determining compliance and ratings. Daylight 

simulation has reached a new plateau in sustainable, 

energy-efficient building design.

The author wishes to acknowledge the following 

people and organizations for their input, creativity, and

assistance during the design and performance 

prediction of the NREL RSF project: Daylighting 

design consultants Michael J. Holtz, Zack Rogers, 

Jennifer Scheib (Architectural Energy Corporation); 

Lighting Designer Rachael Petro (RNL Design); 

Mechanical Engineers David Andary, David Okada, 

Porus Antia (Stantec); Architects Phillip Macey, 

Michael Simpson (RNL Design); Sustainability 

lead/LEED consultant Tom Hootman (RNL Design); 

Radiance tool development and continuous usage 

guidance by Greg Ward (Anyhere Software); Radmap 

development by Francesco Anselmo (ARUP); 

LightLouver product performance assistance by Zack 

Rogers, Michael Plann (LightLouver LLC).

ACKNOWLEDGMENTS

Bourgeois D, Reinhart CF, Ward G (2008). A Standard 

Daylight Coefficient Model for Dynamic 

Daylighting Simulations. Building Research & 

Information 36:1 pp. 68 – 82, 2008

REFERENCES

Crawley, D.; Pless, S.; Torcellini, P. A. (2009). 

Getting to Net Zero. ASHRAE Journal, Sept 

2009. NREL Report No. JA-550-46382. 

http://www.nrel.gov/docs/fy09osti/46382.pdf 

ISO/CIE Joint Standard (2004). ISO 15469:2004 (E) / 

CIE S 011/E:2003Spatial Distribution of Daylight 

- CIE Standard General Sky

Mardaljevic J. (2000). Daylight 

Simulation: Validation, Sky Models and Daylight 

Coefficients. PhD thesis, De Montfort University,

2000

Mardaljevic J. (2000). Beyond Daylight Factors: an 

example study using daylight coefficients. Proc. 

CIBSE National Lighting Conference, York, UK, 

2000, pp. 177-186.

Mardaljevic J. (2000). Simulation of annual 

daylighting profiles for internal 

illuminance.Lighting Research and Technology, 

Vol. 32, No. 3, pp. 111-118

Perez, R., R. Seals and J. Michalsky (1993). An AllWeather Model for Sky Luminance Distribution --

A Preliminary Configuration and Validation. Solar 

Energy 50, 3, pp. 235-245.

Preetham, A.J., Shirley, P., Smits, B.E. (1999). A 

practical analytical model for daylight. In 

Proceedings of Siggraph, 91-100, 1999.

9
Reinhart C F, Breton P-F (2009). Experimental 

Validation of Autodesk 3ds Max Design 2009 and 

Daysim3.0. Leukos 6:1 2009.

Tregenza, P.R., Waters, I.M. (1983). Daylight 

coefficients. Lighting Res. Technol. 15 2 1983, 

pp. 65–71

Ward, Gregory J. (1994). The RADIANCE Lighting 

Simulation and Rendering System. Proc. 

SIGGRAPH, 1994

All images are courtesy of Rob Guglielmetti 

IMAGE CREDITS

10
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4. TITLE AND SUBTITLE

On the Use of Integrated Daylighting and Energy Simulations To 

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14. ABSTRACT (Maximum 200 Words)

This paper illustrates the challenges of integrating rigorous daylight and electric lighting simulation data with wholebuilding energy models, and defends the need for such integration to achieve aggressive energy savings. Through a 

case study example, we examine the ways daylighting – and daylighting simulation – drove the design of a large netzero energy project. We give a detailed review of the daylighting and electric lighting design process for the National 

Renewable Energy Laboratory’s Research Support Facility (RSF), a 220,000 ft2 net-zero energy project the author 

worked on as a daylighting consultant. A review of the issues involved in simulating and validating the daylighting 

performance of the RSF will be detailed, including daylighting simulation, electric lighting control response, and 

integration of Radiance simulation data into the building energy model. Daylighting was a key strategy in reaching the 

contractual energy use goals for the RSF project; the building’s program, layout, orientation and interior/furniture 

design were all influenced by the daylighting design, and simulation was critical in ensuring these many design 

components worked together in an integrated fashion, and would perform as required to meet a very aggressive 

energy performance goal, as expressed in a target energy use intensity.

15. SUBJECT TERMS

energy use intensity; rsf; research support facility; daylighting; simulation; control response

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