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

OpenStudio: An Open Source 

Integrated Analysis Platform

Preprint

R. Guglielmetti, D. Macumber, and N. Long

Presented at Building Simulation 2011

Sydney, Australia

November 14-16, 2011

Conference Paper

NREL/CP-5500-51836

December 2011
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1

OPENSTUDIO: AN OPEN SOURCE INTEGRATED ANALYSIS PLATFORM

Rob Guglielmetti, Dan Macumber, and Nicholas Long

National Renewable Energy Laboratory, Golden, CO USA

High-performance buildings require an integrated 

design approach for all systems to work together 

optimally; systems integration needs to be 

incorporated in the earliest stages of design for 

efforts to be cost and energy-use effective. 

Building designers need a full-featured software 

framework to support rigorous, multidisciplinary 

building simulation. An open source framework—

the OpenStudio Software Development Kit 

(SDK)—is being developed to address this need. 

In this paper, we discuss the needs that drive 

OpenStudio’s system architecture and goals, 

provide a development status report (the SDK is 

currently in alpha release), and present a brief case 

study that illustrates its utility and flexibility.

ABSTRACT

INTRODUCTION

High-performance building design requires an 

integrated design approach to reach ever-loftier 

energy use goals, satisfy more stringent building 

codes, and score well against high-performance

building rating systems. In general, major building 

systems (e.g., lighting and air-conditioning) affect 

each other’s operation and energy flows, so many 

systems and strategies cannot be evaluated as 

individual line items.

Simulation that verifies design performance and 

code compliance has become an essential 

component of the integrated design process. Tools 

such as EnergyPlus (Crawley et al. 2008) and 

Radiance (Ward 1994) rigorously evaluate energy 

and daylighting design strategies and 

technologies, but have not yet been integrated into 

a coherent whole-building simulation

methodology. Major building systems such as 

daylighting controls and HVAC, are well modeled 

by Radiance and EnergyPlus, respectively. They

can no longer be modeled in isolation; however,

simulations, like building designs, must be 

integrated to accurately predict building 

performance (Hirsch et al. 2011).

We present the OpenStudio SDK, an open source 

analysis platform and toolkit that facilitates

integrated whole-building energy analysis.

OpenStudio leverages the EnergyPlus and 

Radiance simulation tools and provides a 

framework for conducting integrated wholebuilding energy analysis. It features a holistic 

building model (.osm) that stores model and site 

data across multiple simulation tools and a fully 

open Application Programming Interface (API). It 

manages simulation parameters across multiple

simulation tools (e.g., EnergyPlus and Radiance), 

and leverages Google SketchUp for graphical user 

interface (GUI)-based CAD input.

PROBLEM STATEMENT

The needs of the building energy simulationist 

extend beyond the simulation community. We 

need to assist designers and engineers, challenge 

status quo building design, enable the testing and 

development of new energy efficiency 

technologies, and promote the evolution of

building energy metrics and codes. A wholebuilding energy simulation toolset is needed to

generate, simulate, and analyze building models. 

It needs to offer:

• Speed

• Simplicity

• GUI interaction

• Integration of multiple simulation engines (for 

increased simulation fidelity of disparate 

systems)

• Command line interface functionality

• Batch processing via GUI or scripts

• Optimization and sensitivity analysis

• Rule-based code compliance checking

• Data display and reporting

These requirements cover a wide spectrum of 

needs and users. Two key concepts for meeting 

these ends are detailed here.
2

Integrated Simulations

EnergyPlus and DOE-2 can produce timely 

results, but have well-known limitations in their

daylight simulation algorithms. Both EnergyPlus 

and DOE-2 engines cannot accurately model 

daylight flux transfer into complex spaces, and 

can model only a limited number of daylight 

redirection technologies. Meanwhile, a fully 

capable daylight and electric lighting simulation 

system—Radiance—has been validated 

(Mardaljevic 2000) and continues to be 

developed; recent additions have facilitated annual 

simulations with arbitrarily deployed complex 

fenestration systems (CFS) (Heshong et al. 2010).

Daylighting and whole-building energy 

simulations have been used successfully in the 

design and validation of high-performance 

buildings (An and Mason 2010, Guglielmetti et al. 

2010). The simulation results from these efforts 

were integrated; however, the simulation process

was not. Multiple designers, architects, and 

engineers, working in multiple offices, 

collaboratively built up the simulation results 

using multiple models that ran through multiple 

simulation programs on multiple computer 

systems and platforms. Despite numerous

coordination conference calls and email messages,

several model/simulation parameters became 

disconnected. An integrated simulation requires an 

easily shared, centralized building model.

Optimization and Automation for Massive 

Insight

An integrated design tool will empower more 

design and engineering firms to produce highperformance buildings. But most new construction 

projects do not have and cannot afford an 

integrated design team, or a sustainable design 

consultant, to guide the process toward a highperformance result. A tool is also needed for

existing buildings, many of which are ripe for 

energy efficiency retrofits. The U.S. Department 

of Energy (DOE 2003) reported that existing 

buildings in the United States numbered 4.9 

million; new construction projects totaled just 

57,000. This disparity has increased in the wake of 

the economic downturn. There is enormous 

opportunity for energy efficiency improvements in 

the existing building stock, yet retrofit projects 

seldom have the budget for a fully integrated 

design team with sophisticated simulation domain 

knowledge to evaluate all the options. 

Stakeholders also often lack the patience to wait 

for minutes or hours for a simulation to run to 

completion, yet they represent—and are 

responsible for—a significant percentage of 

commercial building stock that is ripe for energy 

efficiency improvements.

The Advanced Energy Design Guide (AEDG) 

series (ASHRAE 2011) provides an easier entry 

point for stakeholders by including climatespecific energy efficiency design guidance for a 

number of building types. The recommendations 

are derived from, and backed by, large simulation 

datasets (Hale et al. 2009, Long et al. 2010), 

generated by the automated optimization engine 

Opt-E-Plus (NREL 2010). Unfortunately, many 

would-be energy efficiency champions find the 

AEDGs impenetrable. A “friendlier” front-end to 

these massive data stores, and easier methods for 

researchers and industry to develop them, are

needed. Further, the ability to perform 

multivariate and multiobjective optimization 

analysis should not be the exclusive domain of 

large research facilities, hardware requirements 

notwithstanding.

SOLUTION DESCRIPTION

Overview

OpenStudio is an open source analysis platform 

that facilitates integrated whole-building energy 

analysis. It leverages the EnergyPlus and, 

optionally, the Radiance simulation engines, and 

provides a framework for conducting integrated 

whole-building energy analysis.

OpenStudio is open source under the Lesser GNU 

Public License1

OpenStudio is written in C++; the development 

team embraces object-oriented programming and 

an agile development process. Bindings to C# and 

Ruby are provided via SWIG.

and cross platform, running on 

several Windows, Linux, and Macintosh operating 

systems.

2

A plug-in to Google SketchUp enables users to 

create building geometry and a variety of other 

input data objects needed by EnergyPlus and 

Radiance. All building geometry and simulation 

 1 www.gnu.org/licenses/lgpl.html (accessed July 2011) 2 www.swig.org (accessed May-2011)
3

parameters are stored in a single coordinated 

building model, an OpenStudio Model (.osm).

When desired (or dictated by building shape or 

daylighting technology), Radiance is used either 

with the daylight coefficient method, or to 

generate discrete timestep simulations, to compute

annual daylight availability, glare, and lighting 

control response; this high-resolution analysis of 

the lighting solution is in turn used to inform the 

EnergyPlus model of the electric lighting schedule 

in lieu of using the split flux or radiosity-based 

DElight methods available in EnergyPlus.

A number of GUI applications in the OpenStudio 

Platform facilitate the creation of mechanical 

systems; simulation job and workflow 

management on local workstations and highperformance computing (HPC) clusters; and 

results visualization.

Methods for optimizing economic and energy 

metrics over architectural, and mechanical design 

variables (for instance), and rules-based code 

compliance checking, are under development.

System Architecture

At the core of OpenStudio Platform are the 

OpenStudio Model, its attendant model data 

format (.osm), and objects and methods for 

creating and accessing OpenStudio model objects. 

The design of the OpenStudio Building Model 

was developed in an iterative process in response 

to a list of requirements developed for the overall 

platform. Requirements included:

• Enabling the user to specify a building at 

multiple levels ranging from very high (~10 

parameters for a whole-building model) down 

to the full capabilities of the EnergyPlus 

simulation engine.

• Creating, editing, perturbing, and saving 

building models or individual components.

• Processing external data dictionary-based 

queries (e.g., California’s Title 24 

nomenclature) or other commands for energy 

standards applications.

These requirements are very broad and some 

(such as processing data dictionary commands and 

high-level building parameters) were pulled from

the Building Model and placed in other functional 

blocks of the OpenStudio Architecture (Figure 1) 

(the Standards Interface and Translator blocks,

respectively). The need remained to support twoway translation to EnergyPlus, one-way 

translations to other simulation engines (e.g.,

Radiance), and supporting user interfaces 

(graphical and scripting). Based on these 

requirements, we used the EnergyPlus data model 

as a starting point to develop the OpenStudio 

Building Model. Because other simulation engines 

and user interfaces require new or different data 

than the EnergyPlus data model, the Building 

Model is free to add or subtract data objects that 

are documented to the same level of rigor required 

by EnergyPlus.

Figure 1 – OpenStudio Architecture

Applications

Several applications leverage the OpenStudio 

SDK to give the user access to the Model, set up 

simulation runs, and review data. The first of these 

tools is the OpenStudio SketchUp Plug-in (Figure 

2). This is a continuation of work that began at 

NREL (Ellis et al. 2008) in an attempt to provide a 

simple, GUI-based means to rapidly create 

EnergyPlus geometry input. The Plug-in has been 

extended to support new OpenStudio objects as 

they are added to the model.

Figure 2 – OpenStudio SketchUp Plug-in

Credit: Rob Guglielmetti / NREL
4

Figure 3 depicts some OpenStudio tool options. 

OpenStudio can place new .osm objects (e.g.,

illuminance maps and interior partitions for 

Radiance simulations) and reading and writing 

files in the EnergyPlus input data file format.

Powerful debugging tools, such as the ability to 

render zone surfaces by boundary condition, are 

also available. This render mode and an 

illuminance map are shown in Figure 2.

Figure 3 – OpenStudio Toolbars

SystemOutliner (Figure 4) demonstrates using 

objects and methods exposed by the OpenStudio 

API to graphically edit mechanical systems, which 

has historically been a challenging task for 

EnergyPlus users. The GUI application can 

generate EnergyPlus input for single-zone air 

loops; support for multizone systems is currently 

in development.

Figure 4 – SystemOutliner

RunManager manages simulations spread across 

multiple local processor cores and remote high 

performance computing resources. It currently 

supports EnergyPlus simulations and Ruby scripts. 

Future support for Radiance and other userdefined jobs is planned. Cluster resource 

management is handled with SLURM.

3

The ResultsViewer application (Figure 5) displays 

time series results produced from EnergyPlus 

report variable requests. ResultsViewer reads the 

 3

Simple Linux Utility for Resource Management 

https://computing.llnl.gov/linux/slurm/ (accessed August 18, 

2011)

SQLite database output of the EnergyPlus engine 

and presents the time series data in line and twodimensional flood plots. It also displays the html 

output of EnergyPlus in an internal browser 

window.

Figure 5 – ResultsViewer

Workflows

These applications can be used interchangeably 

throughout a project. A typical workflow would 

begin with using the OpenStudio SketchUp plugin

to create a geometric building model with the 

CAD GUI; the plug-in also includes templates for

rapidly populating the model with valid 

mechanical systems. SystemOutliner could then

be used to visually create custom single-zone 

mechanical systems. Once the user has an 

OpenStudio model, they could use the 

RunManager GUI to set up a series of simulations, 

or use Ruby scripts to access the perturbation and 

rules processing methods available in OpenStudio.

(RunManager can also be used from the command 

line and within Ruby scripts as needed.) Results 

are then viewed in ResultsViewer.

EnergyPlus – Radiance Integration

As mentioned in the Introduction, the daylight 

simulation algorithms in EnergyPlus and DOE-2 

have limitations. Reinhart and Jones (2004) 

illustrated that the differences in predicted interior 

illuminances between DOE-2 and Radiance-based 

DAYSIM were significant, leading to an 

overstatement of the potential energy savings of a 

given design. Koti and Addison (2007) found 

similar results, and proposed “aiding” DOE-2 with 

DAYSIM-calculated data. They essentially 

informed the energy simulation of the lighting 

systems’ daylight response determined by a 

Radiance-based simulation; this methodology is 

currently in use by practitioners attempting to 

Credit: Rob Guglielmetti / NREL

Credit: Rob Guglielmetti / NREL

Credit: Rob Guglielmetti / NREL
5

integrate energy and daylighting simulations (An 

and Mason 2010).

As DAYSIM and EnergyPlus determine lighting 

power reductions based directly on the work plane 

sensor point illuminance, the photosensor 

controlling the lighting system (which would 

actually be located on the ceiling) is assumed to 

have a precise cosine spatial response and be 

“ideally commissioned” to send the proper

response to the lighting control system. The work

plane sensor point is assumed to be truly 

representative of the critical task illuminance set

point. In practice, none of these criteria are likely 

to be met.

The SPOT tool (Architectural Energy Corporation 

2008) was created to address this gap. This 

Radiance-based simulation more faithfully 

represents a daylight-responsive lighting control 

system, where the photosensor is located 

realistically and is commissioned to “read” the 

task illuminance or another input that has been 

determined to correlate to the task. SPOT also 

models the interaction of discrete luminaire 

zones—a subtle and often confounding factor in 

commissioning the lighting control systems in real 

buildings. SPOT offers an option to save a DOE-2 

function file from an annual simulation, to 

facilitate the “assistance” process described by 

Koti and Addison (2007); Guglielmetti et al. 

(2010) used this successfully on a recent project.

Scheib et al. (in press 2011) further investigated 

the limitations of EnergyPlus’ simulation 

capabilities. They used the Radiance-based SPOT 

software to conduct a Radiance daylight 

simulation and calculate the true photosensor 

response. They found that calibration factors 

could be derived from a limited set of SPOT 

simulations that could be applied to the 

EnergyPlus computed daylight values. This raises 

the possibility of using Radiance to compute 

daylight solutions over a limited range of seasonal 

conditions and applying those results to the much 

more rapidly computable daylight solutions 

produced by EnergyPlus.

All this illustrates that although the daylight 

calculation in Radiance certainly has value, the 

electric lighting and control simulations are

critical to demonstrating the efficacy of a given 

daylighting design or system. It is expensive to 

compute, but we believe there may be ways to use 

Radiance judiciously to overlay rigorous 

daylighting simulation on larger EnergyPlussimulated parameter spaces. Many daylighting 

strategies also take architectural forms that 

EnergyPlus cannot handle, and technologies that 

cannot be evaluated using the EnergyPlus 

algorithms (because they involve specular 

surfaces, for instance). For such cases, a rigorous 

lighting simulation is required.

The time burden of the ray tracing calculations

done by Radiance has been called into question.

EnergyPlus can compute the daylighting solution 

for a time step in seconds, whereas a Radiance 

simulation can take several minutes to several 

hours. Recent additions to the Radiance suite 

enable the simulationist to apply the daylight 

coefficient approach (Tregenza and Waters 1983) 

to the problem of annual daylight simulation 

(Bourgeois et al. 2008), and use bidirectional 

scattering distribution functions (BSDFs) to 

describe complex fenestration systems and 

arbitrary window treatments (blinds, shades) in an 

annual daylighting context (Saxena et al. 2010, 

Ward et al. 2010). Although the Radiance 

simulations take longer than the EnergyPlus

simulations for the same building, the Radiance 

results are of much better quality. Radiance can

also generate high dynamic range images, suitable 

for qualitative evaluation, visualization, and glare 

analysis of a daylighting design.

For all these reasons, the integration of Radiance 

and EnergyPlus simulations has been a key 

requirement for the OpenStudio project.

The first step toward this end is to add objects and 

methods to the OpenStudio Model to support 

daylighting analysis. For example, EnergyPlus 

models are generally discretized into thermal 

zones; OpenStudio models also follow this 

convention. But when evaluating daylight 

traversal through a building model, the thermal 

zone boundaries do not necessarily align with 

architectural massing. To address this issue, an air 

wall construction denotes a thermal zone 

boundary that has no architectural counterpart. 

Conversely, objects are also needed to represent 

internal objects (e.g., interior walls, furniture, 

cubicles, and partitions) as they exist in the space 

plan; such objects are implemented in OpenStudio 

as internal partition objects. Figure 6 depicts an 

OpenStudio model with typical energy model 
6

geometric detail; Figure 7 shows the same model 

with the additional OpenStudio objects needed for 

a proper Radiance simulation. The industry 

standard practice of representing energy model 

geometry using infinitely thin wall constructions 

is a further hindrance to producing representative 

Radiance models from EnergyPlus-type input. 

Support for wall thickness in the Radiance models 

is planned, using either additional internal

partition objects, shading elements, or BSDFs.

Figure 6 – Typical Energy Model (.idf) Viewed in 

OpenStudio with Solid Thermal Zone Boundaries

Figure 7 – OpenStudio Model (.osm) with Air 

Wall Constructions, Internal Partitions and 

Luminaire Objects for Radiance Simulation

Calculation grids and photosensors (referred to as 

illuminance maps and daylight sensors, 

respectively) are available for placement in the 

model, and a framework for individual luminaire 

placement (and association to photometric 

distributions (.ies files) is under development. 

These objects are all placed or assigned via the 

OpenStudio SketchUp Plug-in GUI interface. 

Lastly, a series of scripts were developed to

support Radiance analysis in OpenStudio:

• ModelToRad.rb converts an OpenStudio 

.osm model to a valid Radiance model. 

Geometry, material properties, site, and 

weather file information are all derived from 

the .osm, and valid Radiance objects and 

materials are created. Currently, only

Radiance materials “plastic” and “glass” are 

supported; support for “trans” and the new 

“bsdf” materials is planned. Air wall

constructions are ignored, and illuminance 

maps and daylight sensors are exported in 

standard Radiance point/vector arrays. 

Aperture polygons (e.g., windows and glass 

doors) are grouped by orientation to facilitate 

three-phase daylight coefficient matrix 

binning.

• DaylightSim.rb enables the user to perform a 

variety of simulations with Radiance tools on 

the converted OpenStudio model. Time step 

simulations (of views or illuminance maps) 

are available using standard Radiance tools 

(e.g., rtrace and rpict), and daylight 

coefficients can be computed (simple daylight 

matrix). An annual simulation mode and 

complete support for the three-phase method 

with BSDF support is under development.

We used the OpenStudio API to rapidly prototype 

this functionality in Ruby and demonstrate the 

general utility of the OpenStudio libraries. The 

functionality contained in these scripts will 

ultimately be reimplemented in C++ as part of the 

OpenStudio core.

Optimization

Ellis et al. (2006) demonstrated that simulation 

can be used to navigate large parameter spaces in 

support of optimization analysis for a variety of 

building types and program goals. They used OptE-Plus, a noncommercially available research tool 

(NREL 2010).

The optimization algorithm used in Opt-E-Plus is 

being ported to OpenStudio to make it publicly 

available. The Sequential Search algorithm 

operates on bi-objective optimization problems 

over categorical variables. Typically, the two 

objective functions of interest are cost and energy 

savings. Additional optimization and uncertainty 

handling features are under development. For 

large problems, effective use of these features will 

often require access to cluster, cloud, or 

supercomputing resources (not all of which are yet 

supported by RunManager).

Components containing model data and rules for 

applying those data to a model will be stored in an 

online Building Component Library (BCL), which

will enable users to use community vetted data to 

more quickly assemble models and design 

problems.

Credit: Rob Guglielmetti / NREL

Credit: Rob Guglielmetti / NREL
7

APPLICATION

179D Tax Deduction Quick Estimate Tool

As an example of the utility of the OpenStudio 

Platform, we present a brief case study of its 

application to the creation of a large dataset for a 

DOE request.

As part of an initiative to promote energy 

efficiency in U.S. buildings, DOE requested a 

Web-based tool that would simplify the 

determination of eligibility for a tax deduction. 

Section 179D of the U.S. Tax Code provides tax 

deductions to builders, owners, and lessors who 

implement energy efficiency measures (EEMs) in 

commercial buildings. DOE’s vision was to 

provide stakeholders an easy means to evaluate 

various EEMs on their own buildings against the 

tax credit requirements, and quickly report success 

or failure. The Web-based front end accepts

simple inputs, and relies on a large precomputed 

energy analysis dataset for instantaneous 

reporting. The initial version of the tool 

considered lighting, HVAC, and envelope EEMs

only and on an individual basis; nonetheless, 

given the number of building types covered by the 

tax credit, it was still necessary to analyze a large 

number of cases. The parameter space was:

• 12 building types

• 16 climate zones

• 92–1009 HVAC perturbations (depending on 

building type and climate)

• 92–1009 envelope perturbations (depending 

on building type and climate)

• 4 lighting perturbations

This dictated a final count of 226,867 simulations, 

which were run in a series of batch jobs. NREL 

researchers used the OpenStudio Ruby bindings to 

automate the process of creating and simulating 

these models using NREL’s Red Rock HPC 

cluster. All simulations were run in approximately 

one week. The entire project (assignment, 

simulation, data fit, Web front-end programming,

and going live) was completed in approximately 

one month (NREL 2011).

Conclusions and Future work

We have presented an integrated open source, 

cross-platform analysis platform for highperformance building design that leverages the 

EnergyPlus and Radiance simulation engines. A 

holistic model—the OpenStudio object model—

contains all model geometry and other input 

parameters, and several applications are enabled 

by this object-oriented framework for creating 

building energy models. An API provides

programmatic access in C++, Ruby, and C#.

We have argued for more thorough daylighting 

analysis than is currently offered in energy 

analysis software, citing evidence that daylighting 

simulation tools are required to produce highperformance building designs whose instantiations 

meet the lofty goals set at the beginning of a 

project. Integrated daylighting and energy 

simulation analysis is supported by the holistic 

OpenStudio building model, which specifically

supports EnergyPlus and Radiance model objects 

and inputs.

The work to integrate Radiance simulation 

capabilities into OpenStudio workflows is 

ongoing. There is currently one-way translation 

from .osm to Radiance format, but support for all 

relevant OpenStudio model objects (and Radiance 

materials) requires further development. The 

ability to set Radiance simulation parameters from 

the GUI is currently unavailable. These 

parameters are not stored in the model; this 

support will be added. Radiance simulation 

parameterization guidance for end users is also 

needed, and is planned for future releases.

With the addition of new OpenStudio objects,

several geometric model simplifications inherent 

to energy models, but inaccurate for daylighting 

simulations, have been overcome for Radianceready models. We recognize that infinitely thin 

wall constructions still present an unacceptable 

simplification for rigorous daylight simulation.

This will be addressed by adding wall thickness 

and skylight well geometry directly to the 

OpenStudio model, or by representing this 

geometry as BSDFs automatically upon model 

conversion.

The creation of a robust, multiapplication analysis 

platform has by necessity been rather inward and 

developer focused. The framework and the API 

are now at the point where rapid prototyping and 

testing of additional functionality will be 

relatively easy. As this is an open source project, 

we invite the simulation community to join us in 

refining, testing, and extending OpenStudio.
8

ACKNOWLEDGEMENTS

The authors would like to thank the entire NREL 

OpenStudio development team for their work on 

this project, in particular: Kyle Benne, Elaine 

Hale, Evan Weaver, Katherine Fleming, David 

Goldwasser, and Marjorie Schott; Brent Griffith 

for his work on the 179D tax tool and willingness 

to share his EnergyPlus expertise; and Larry 

Brackney and Luigi Gentile Polese for their 

leadership and management of this software 

project and development team.

Further thanks to Greg Ward of Anyhere 

Software, Andrew McNeil of Lawrence Berkeley 

National Laboratory, and Axel Jacobs of London 

Metropolitan University, for Radiance tool 

development, validation work, and usage 

references.

This work was supported by the U.S. Department 

of Energy under Contract No. DE-AC36-08-

GO28308 with the National Renewable Energy 

Laboratory.
9

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