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Contract No. DE-AC36-08GO28308

Enabling Detailed Energy 

Analyses via the Technology 

Performance Exchange

Preprint

Daniel Studer, Katherine Fleming, 

Edwin Lee, and William Livingood

To be presented at the 2014 ACEEE Summer Study on Energy 

Efficiency in Buildings

Pacific Grove, California

August 17–22, 2014

Conference Paper

NREL/CP-5500-61404

August 2014
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Enabling Detailed Energy Analyses via the 

Technology Performance Exchange

Daniel Studer, Katherine Fleming, Edwin Lee, and William Livingood, 

National Renewable Energy Laboratory1

ABSTRACT

A key tenet to increasing adoption of energy efficiency solutions in the built environment 

is improving confidence in energy performance. Industry currently uses predictive modeling, 

often via detailed hourly or sub-hourly energy simulation programs, to account for site-specific 

parameters (e.g., climate zone, hours of operation, and space type) and arrive at a performance 

estimate. Such methods are highly precise; however, they invariably provide less than ideal 

accuracy because high-quality, foundational energy performance input data are lacking.

The Technology Performance ExchangeTM—a free, publically accessible Web-based 

portal—was constructed to allow the transparent sharing of foundational, product-specific energy 

performance data. It leverages significant external engineering efforts and a modular architecture 

to agnostically identify and codify the minimum information necessary to accurately predict 

product energy performance and represents a novel solution to the problem mentioned above. 

Additionally, by translating contributed foundational data into energy modeling syntax, the 

Technology Performance Exchange provides an actionable and concrete resource, allowing 

energy modelers to improve model accuracy, drive energy efficiency decisions, and reduce 

development time and cost.

This paper (1) presents a high-level overview of the project drivers and the structure of 

the Technology Performance Exchange; (2) offers a detailed examination of how technologies 

are incorporated and translated into energy modeling syntax; and (3) examines several ways that 

this workflow translates energy performance data into actionable energy savings.

Introduction

When building energy modelers investigate products and technologies that claim to 

increase energy efficiency, they often find that they lack access to what are perceived as credible 

energy performance data. Even if they move forward with an analysis, the assumptions they must 

make about product performance (above and beyond those that detail how a product will be 

used; e.g., a representative operating schedule) reduce the accuracy of the prediction. Therefore, 

even if modelers determine that a product would likely provide an acceptable increase in 

efficiency, they often have difficulty convincing their clients to move forward with a project 

because they cannot support the development of a quality business case. This holds true even if 

measured data for previous applications of a product are available. The use of case-study data to 

 1 The Alliance for Sustainable Energy, LLC (Alliance), is the manager and operator of the National Renewable 

Energy Laboratory (NREL). Employees of the Alliance for Sustainable Energy, LLC, under Contract No. DEAC36-08GO28308 with the U.S. Dept. of Energy, have authored this work. The United States Government retains 

and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a 

non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or 

allow others to do so, for United States Government purposes.
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predict performance in an alternative building is difficult because such data are usually 

intertwined with nonapplicable site- and operation-specific parameters.

This is not to say that energy performance data are not available. Generally, product 

manufacturers provide some level of energy performance data for their products. Sometimes 

these data are sufficient to support detailed building- and use-case-specific energy performance 

analyses. But for many technologies, this is not the case.

To facilitate improved identification, storage, and sharing of foundational energy 

performance data, the U.S. Department of Energy’s (DOE) Building Technologies Office and 

Federal Energy Management Program, and the Bonneville Power Administration (BPA) funded 

the National Renewable Energy Laboratory (NREL) to develop the Technology Performance 

ExchangeTM (TPExTM; NREL 2014c). The TPEx is a free, publically accessible Web-based 

portal that serves as a centralized repository for users to share and find product-specific energy 

performance data. Additionally, within certain technology categories, contributed foundational 

TPEx data are automatically translated into EnergyPlus (DOE 2013) input objects and stored on 

the Building Component Library (BCL; NREL 2014a) where they are immediately accessible to 

users of a variety of public and private sector tools.

This paper provides a brief overview of the TPEx, including a discussion of how data 

verification challenges were overcome and the workflows implemented to provide open and 

transparent data exchange. This introduction is followed by a detailed description of how 

foundational TPEx data are translated into EnergyPlus input objects and stored on the BCL. 

Finally, a discussion is presented that highlights the benefits of this workflow.

The Technology Performance Exchange

Because the building technology landscape is dynamic, with new technologies and 

products being brought regularly to market, it is important to ensure that DOE, BPA, NREL, and 

external stakeholders can easily add new technologies and products into the TPEx. To allow new 

technologies to be added over time, the TPEx consists of two pieces: 

• The core infrastructure. This Web-accessible software nucleus acts as a foundation, 

providing the services that any user would expect from an information portal, including 

data indexing, user-driven queries, user registration/account access, and data 

upload/download pathways.

• Data entry forms (DEFs). The core infrastructure was built to accept the overlay of any 

number of technology categories via the development of DEFs, which identify “the 

minimum product-specific energy performance characteristics and other critical 

properties necessary to evaluate a product’s energy performance” (Studer and Lee 2013). 

Adding a technology category to the TPEx enables product-specific energy performance 

data to be uploaded and shared. DEFs are similar in aim to the annexes being developed 

to the as-yet unpublished Standard 205 within ASHRAE Standard Project Committee 205 

– Standard Representation of Performance Simulation Data for HVAC&R and Other 

Facility Equipment (ASHRAE 2013). Current plans call for applicable TPEx DEFs to 

align with the ASHRAE Standard 205 annexes, as they are published.

This combination enables the TPEx to function as an expandable—but agnostic—data 

clearinghouse. With a robust foundation on which to build, new technologies can be added as the 

appropriate energy performance characteristics are identified.
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Data Provenance

Of paramount importance during the project was ensuring the credibility of the data 

housed in the TPEx. The idea of vetting uploaded performance data was dismissed because (1) it 

would not be practical or sustainable for any entity to validate all uploaded data; and (2) barring 

conflict with the laws of thermodynamics, there is no reasonably defensible ground for any entity 

to claim that any other user’s data are invalid or otherwise incorrect.

With no practical method to ensure data validity, an alternative was sought. The 

implemented solution deals with the issue via a less traditional approach, using a combination of 

constrained workflows and metadata to ensure that TPEx end users can decide for themselves

whether to trust the uploaded data. These will be discussed below.

Workflow Restrictions. Before TPEx users can upload performance data, they must first 

register using one of three registration options: Manufacturer/Brand Owner, Third-Party Test 

Laboratory, or Contributing Evaluator. Registration requires association with an organization; 

all new organizations are reviewed and must be approved by an administrator for a user to 

contribute content to the TPEx.

Each registration option has a unique set of allowed behaviors or workflows. The use of 

numerous registration types (1) helps to prevent intentional misrepresentation (either through 

over- or understatements) of product performance; and (2) provides background information that 

TPEx users can refer to when deciding whether to use posted data.

Metadata. To empower all TPEx users to make informed decisions about which, if any, 

performance data to use in product or technology energy analyses, the TPEx displays a host of 

additional information related to product performance data provenance (see Figure 1). Referred 

to as metadata, the following information is displayed alongside each piece of performance data:

1. The name of the organization that uploaded the data.

2. The date the performance data were uploaded.

3. The data derivation method. Options are chosen from an enumerated list and associated 

with each data parameter (not just a dataset).

4. The registration type of the contributing organization, denoted as a graphical icon.

Figure 1. This TPEx screenshot shows metadata displayed in conjunction with product performance data. The 

scale icon (right) indicates that NREL is registered as a Contributing Evaluator. Source: Daniel Studer, NREL.

When TPEx users download performance data from the site, the metadata are 

downloaded as well (whether the data are accessed through the user interface [UI] or through the 

application programming interface [API]). This ensures that TPEx users can make informed 

decisions about the information they choose to use in analyses, even if those data are not 

obtained directly from the TPEx (e.g., forwarded from a TPEx user to another individual, or 

accessed via a third-party data portal that references TPEx data).
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Data Accessibility

Because the TPEx is meant to be a mechanism through which data are actively shared, 

two mechanisms were created to facilitate easier data access: a Web interface (the UI) and an 

API. Figure 2 provides a graphical representation of how users interact with the TPEx.

Figure 2. This diagram provides an overview of how TPEx end users contribute and access performance data: 

(a) directly via the UI, or (b) by accessing the TPEx API via user-created scripts. Note that the integration of 

TPEx data into third-party applications and databases (bottom right) is encouraged. Source: Marjorie Schott, 

NREL.

Application Programming Interface

The TPEx API enables users to automate interaction with TPEx data. Users can 

automatically query the TPEx database via the TPEx API search, download, and fields resources 

and download any or all performance and metadata for products of interest. TPEx users can also 

automate the upload of product and performance data (contingent on their registration type).

Web Interface

The TPEx UI, shown in Figure 3, provides similar, though manual, capabilities to the 

TPEx API. Users can browse technology categories, search for products, and download energy 

performance and metadata via the UI. However, two main features available through the TPEx 

Web interface are not available through the API: (1) users can easily track and maintain (edit, 

update, or delete) their product or performance data submissions as part of their account pages; 
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and (2) users can compare up to four products in any technology category side-by-side. This 

comparison feature is helpful if a user is investigating only a handful of products and desires an 

easy way to compare performance.

Figure 3. Screenshot showing the TPEx UI. Source: Daniel Studer, NREL.

The Building Component Library

As mentioned earlier, certain TPEx technology categories are automatically translated 

into EnergyPlus input objects and stored in the BCL, an online, searchable repository of building 

energy model inputs that (1) encourages the sharing and reuse of energy modeling code; and (2) 

increases the transparency and reproducibility of energy simulation results. The BCL is currently 

being leveraged by many public and private sector tools, including DOE’s modeling platform, 

OpenStudio (NREL 2014b), DOE’s Asset Score (DOE 2014), and simuwatt (concept3D 2014).

The BCL primarily stores data termed components, which represent the primary building 

blocks necessary to construct an energy model. Examples include representations of physical 

components (either generic instances or specific products such as windows, walls, and HVAC 

subsystems) as well as ancillary information needed to complete an energy modeling simulation, 

such as weather data and operating schedules. BCL components are categorized using a specific 

BCL taxonomy term, or type. Components also include descriptive attributes that further identify 

the components and serve as facets to efficiently filter results when searching for a particular 

component on the site. A component includes associated payload files that are representations of 

the component in terms of one or more specific modeling software packages; payload files can 

be added directly to an energy model. Although payload files of any type can be stored in the 
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BCL, most components currently contain either EnergyPlus (.idf) or OpenStudio (.osm) 

payloads.

The BCL can also store energy conservation measures. Measures represent a change that 

can be applied to a current building energy model, either by modifying a component or 

characteristic of the model, or by adding and removing components. As with components, BCL 

measures are categorized according to the BCL measure taxonomy, contain associated payload 

files, and use attributes to describe the measure and enhance search functionality. BCL measures 

consist of Ruby scripts that perform operations on an OpenStudio building energy model along 

with related spreadsheets that contain reference information.

BCL users who are registered as members of an approved organization can contribute 

content to the BCL. Similar to TPEx, content that users upload is associated with their respective 

organizations, although uploaded BCL data are accessible by group members only, until a group 

moderator decides to publish it. In addition to its Web interface, the BCL also provides an API 

that can be used to upload and update content, as well as to search for and download components 

and measures. 

For more information about the BCL, please see NREL (2014a), Fleming, Long, and 

Swindler (2012), and Long, Fleming, and Brackney (2011).

Data Translation

TPEx and BCL API users can automate data queries, data aggregation/synthesis, and 

energy modeling based analyses. This last approach is currently being pursued by BPA, which 

sponsored the work to automate the translation of products within specific TPEx technology 

categories into publically accessible EnergyPlus input objects (Studer and Lee 2013).

This section describes in detail the process employed to facilitate this translation, 

including the decisions implemented to handle multiple or malformed datasets to generate a 

single, usable EnergyPlus product representation. 

Discussion of Product Representation

The performance of a single “real-life” product can be represented in many ways. In the 

TPEx to EnergyPlus translation process, the TPEx representation is initially composed of energy 

performance parameter values (possibly containing duplicate entries) and performance maps that 

specify the performance of the product over a variety of conditions. The translator’s purpose is to 

convert this tool-agnostic representation into a form that is ready for inclusion in the BCL, and 

ultimately in a specific simulation tool (in this case EnergyPlus).

In some modeling applications, it may be sufficient to include only rated conditions in a 

simulation model formulation. This approach may be useful when detailed performance data are 

very difficult to obtain, or when the model formulation is required to be highly simplified. In 

such cases, provisions may be included to handle off-design conditions.

When using detailed simulation programs such as EnergyPlus, detailed component 

performance data over a variety of conditions are necessary to provide an accurate result. This 

minimum information criterion is strongly considered when determining whether a product’s 

TPEx representation is sufficient for translation.
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From Foundational Data to EnergyPlus Object

The TPEx data to EnergyPlus object translation process is composed of several steps, 

illustrated at a high level in Figure 4. The translator is composed of a set of scripts that perform 

database and mathematical operations. The translator is extensible to allow easy implementation 

of new product categories. Currently, the translator can convert heat pump water heater (HPWH) 

and ductless heat pump (DHP) system TPEx data (including variable refrigerant flow systems), 

into EnergyPlus objects.

Figure 4. Overview of the process used to convert product-specific foundational energy performance data from the 

TPEx to EnergyPlus syntax. Source: Marjorie Schott, NREL.

The data the translator initially retrieves consist of all the product and performance data 

available on TPEx for that particular product. This can include multiple values for any given 

performance parameter as well as multiple performance maps. The translator attempts to 

aggregate the entirety of the data into a single EnergyPlus representation of the product. The 

resulting EnergyPlus files are then pushed to the BCL; this last step is detailed in a later section.

The translation process consists of four high-level tasks:

1. The translator retrieves the TPEx dataset for a single product (all product and 

performance data, including performance maps) and unpacks it into a directory hierarchy. 

This structure is immediately validated to ensure the process can continue.

2. Performance parameter data are aggregated (if applicable) from the raw-text summary 

file that is generated as part of Step 1. Additional validation checks are run to ensure that 

critical performance parameter data are present.

3. When present, performance map files are individually transformed into a new format. If a 

product has multiple maps, the files are merged to create a single representative dataset. 

This dataset is then examined to ensure enough data are available to proceed. 

4. If the translation to this point has been successful (no errors), the translator completes the 

process by writing the aggregated performance data and performance map data as a 

single EnergyPlus object.

The TPEx API uses software scripts that enable this translation to be automated. Currently, 

the process is repeated nightly for all products in the HPWH and DHP technology categories. 

The translator processes only files that have been updated since the last processing period.

Aggregating Multiple TPEx Datasets

As mentioned above, TPEx data for a particular product may include performance 

parameter data and performance maps, although in some instances only one or the other may be 

present. Additionally, multiple values for one or many parameters, or multiple performance maps 

may be present for a particular product. Because the TPEx to EnergyPlus translator seeks to 
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create a single representation for each product, and not a representation for each TPEx dataset, 

the translator can aggregate the data.

In keeping with the TPEx’s data validation philosophy, the translator does not attempt to 

determine whether any given data value is correct. Instead, a weighted-average approach is 

employed to create a single representative value when multiple parameter values are found (Step 

2). When any given parameter has multiple data values, the following equation is used to 

calculate a weighted average:

x� = ∑i βixi

∑i βi

Where: x = A numeric performance parameter value

β = Weighting factor for this parameter

By assigning each performance parameter value, x, a weight, β, according to its data 

source type, a single weighted average for that parameter is obtained. Values entered by 

Manufacturers/Brand Owners and Contributing Evaluators are assigned weights of 1.0. ThirdParty Test Laboratory-entered data are assigned weighting factors of 1.2. Because of the 

equation used, only the relative values of the weighting factors (not their absolute values) are 

important.

Performance map data are treated similarly (Step 3). When a particular product has 

multiple performance maps, data that are blatantly invalid (non-numeric, for example) are first 

pruned. Then, for each performance map point, values are aggregated using the same weighting 

factors used to aggregate performance parameter values. TPEx users may enter partially 

completed performance maps. This means that the final, aggregated performance map may 

contain voids and averaged data values.

Data Validation

Data are validated in multiple stages during the entire TPEx to EnergyPlus translation 

process. Although not explicitly labeled in Figure 4, data are validated in each step. Figure 5 lists 

the validation checks that are run during Steps 2 and 3 of the translation process; decision points 

illustrate the reasons that a product passes or fails validation. Because energy performance 

parameters are validated against a set of basic rules (i.e., some inputs are required to be numeric) 

when they are first entered in the TPEx, the translator does not repeat this. Performance map 

data, however, are not validated on TPEx, so the translator validates these data.

During Steps 2 and 3, after the performance parameter or performance map dataset for a 

given product has been aggregated into a single representation (if necessary) and been verified as 

sufficient, the translator validates the quality of the data. This is not a thermodynamic evaluation,

but rather a step to ensure a useful translation can occur. The translator checks to see whether 

sufficient performance parameter or performance map data are available to proceed with 

translation to an EnergyPlus object.

For each TPEx technology category, certain performance parameters are identified as 

critical. If the aggregated product representation does not include a value for any of these, the 

translator cannot provide a useful EnergyPlus object, so the process is terminated for that 

product.2

 2 Even though the process stops for this product, a log is always maintained to allow inspection of components that 

fail the translation process.
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Figure 5. Overview of the data aggregation and validation steps employed in the translation process from TPEx 

data to EnergyPlus input syntax. Source: Marjorie Schott, NREL.

Instead of a single data point, a minimum fraction of the requested performance map data 

must be present in the aggregated performance map to generate a usable curve or lookup table 

representation for that product. For an actual dataset A, with a performance map template that 

defines a possible set B and a minimum tolerance for dataset size ε, the decision for determining 

whether to continue is described as: 

Continue = � True, if ∶ A� ≥ B�ε

False, if ∶ A� < B�ε

Many products on the TPEx may include multidimensional performance maps, where 

dependent variables are requested for a combination of multiple independent variables. For 

example, if a product’s energy performance is dependent on three independent variables, the 

performance map is defined to include the performance of the unit in response to many 

permutations of the independent variables to best capture the performance representation:

Z = f(x⃗)

After translation, however, the final EnergyPlus formulation must instead represent the 

product’s performance using individual curves, each of which is dependent on a single element 

in x⃗, while holding all other elements constant:

Zi = f(xi); for all i
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As such, when products use multidimensional performance maps as part of the TPEx 

product representation, the TPEx to EnergyPlus translator examines each dimension to verify 

that each curve contains sufficient data to be represented in the final form.

Creating Translated Objects

Once the TPEx dataset has been aggregated and validated, the translator writes the 

product representation in the desired form (Step 4), which in this case is EnergyPlus. The 

EnergyPlus syntax consists of a comma/semicolon delimited list of input data. Simulationists can 

use this set of inputs as necessary as a component in their own building and system simulations.

Pushing Content to BCL

Once TPEx performance parameter and performance map data have been aggregated and 

translated into EnergyPlus product representations, a separate script is used to package the 

resulting files into BCL components (Step 5).

Each BCL component package includes an xml file that contains descriptive information 

about the component and about the building energy model file representing the product. The xml 

file generated using the script contains the name of the component (which matches the TPEx 

product name), a description of the component, and source information linking the BCL 

component back to the product’s TPEx URL and unique identifier (uuid). Other pieces of 

identifying information such as the product manufacturer, brand, product line/family name, 

model number, and a subset of the technology category-specific performance data are also stored 

as BCL component attributes.

Not all performance parameter data stored on the TPEx are used as BCL attributes; only 

the information most relevant to the energy model representation of the product. These attributes 

are used to describe the component and to filter search results on the BCL. Each BCL component 

is associated with a specific component type representing the component’s technology category. 

The BCL’s component types and the TPEx’s technology categories are derived from the same 

taxonomy, so the mapping of technology categories to component types is trivial. This 

information is also stored in the xml file. Lastly, a reference to each payload file associated with 

the component, along with the file’s associated software program and version, is stored in the 

xml. Although BCL component files can be any building energy model files or other files 

relevant to the model, the TPEx translated components contain EnergyPlus model files. 

All this information is packaged into either a zip or a tar.gz file and uploaded to the BCL 

via the BCL API. Users must be part of an approved organization to publish content on the BCL, 

so all TPEx products are uploaded to the NREL TPEx group.

The Process From Start to Finish

The complete TPEx to BCL workflow is described in Figure 6. The TPEx search API 

resource is first used to retrieve products (in the relevant technology categories) that have been 

created or updated since the script was last run. The TPEx download API resource is then used to 

download all performance data and files associated with each returned TPEx product. This 

information is input into the translation module, which then processes the information to create 

an EnergyPlus model file representing the product. If the translation module deems the 

information is insufficient to create an EnergyPlus file, the process is aborted and no BCL 
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component is created. If a file is created, it is then used—along with the downloaded TPEx 

product data—to create a BCL component package. The product’s TPEx uuid is used in the BCL 

search API resource to determine whether the BCL already has a component matching the TPEx 

product. If it does, the component package updates that component. Otherwise, the component 

package creates a new component. This entire procedure is run automatically each night.

Figure 6. A high-level description of the entire TPEx to BCL workflow. Source: Marjorie Schott, NREL.

Workflow Benefits

The TPEx interface mechanisms (the UI and API) and the TPEx to BCL workflow were 

developed to enable interested parties to use and share large amounts of relevant energy 

performance data efficiently. Although the translation mechanism was developed specifically to 

support the energy modeling community (and is the main subject of this paper), the TPEx was 

designed to support a broad set of users. The following sections detail several possible use cases.

Data Contributors

Product manufacturers sometimes face an uphill battle convincing potential customers 

that their products provide cost-effective and environmentally friendly solutions to the 

customer’s needs. Because the DEF development process ensures that the parameters the TPEx 

accepts are systematically identified, manufacturers can help to assuage customers’ product 
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performance doubts by providing energy performance data to the TPEx. The TPEx API allows 

manufacturers to efficiently upload entire product catalogs.

Many electric and gas utilities currently oversee or participate in technology field 

demonstrations to assess technology energy performance. These programs are used to identify 

technologies that are likely to provide demand or energy reduction, but common practices make 

it difficult to share test results in a meaningful way. Although project summary reports and 

aggregated analyses are published and shared, innate differences between utility service 

territories (climate, generation mix, demand profiles, prevalence of building type, etc.) often 

preclude the rote application of demonstration results from one utility to another.

The TPEx’s standardized structure to share measured foundational energy performance 

data (i.e., characterized product performance) provides a mechanism through which multiple 

utilities can collaborate to avoid duplication of effort and reduce total project time and cost. By 

co-sponsoring field testing efforts, or by using an alternative round-robin style technology 

demonstration approach to increase the number of examined technologies, utilities can leverage a 

common set of measured data and then apply utility-specific characteristics (weather data, 

region-specific usage patterns, etc.) to the data during the evaluation process.

Data Users

By providing a central, standardized repository for tool-agnostic energy performance 

data, the TPEx increases the likelihood that required input data will be available for any user to 

leverage in their own analysis. Whether helping energy modelers to reduce their need to use rules 

of thumb, or simply providing the high-level information a user needs to perform a “back of the 

envelope” calculation, the TPEx provides the data necessary to drive those calculations.

The true analytical power of the TPEx is most likely to be realized by users who take 

advantage of the site’s integration with the BCL. By automatically generating EnergyPlus input 

files from the raw performance data, energy modelers (1) don’t have to spend the time 

constructing product representation themselves (or settling for “close-enough” solutions); and (2) 

are assured that the resulting product representation is based on real, available, and transparent 

data. Additionally, by storing the resulting EnergyPlus product representations on the BCL, users 

can more easily take advantage of other tools built on top of DOE’s modeling platform,

OpenStudio, which provides additional analysis benefits.

Figure 7 illustrates the workflows enabled by TPEx, BCL, EnergyPlus, and OpenStudio 

integration.
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Figure 7. Diagram illustrating the workflows enabled by integrating the TPEx with the BCL, and indirectly with 

EnergyPlus and OpenStudio. TPEx users are free to leverage the evaluation-tool agnostic data using the TPEx UI 

or API, or take advantage of translated data that are stored on the BCL. Source: Marjorie Schott, NREL.

Conclusion

Many stakeholders are interested in adopting energy efficiency solutions in the built 

environment, but up to now have lacked the energy performance data to determine whether these 

solutions are cost effective. With stakeholders unable to identify whether particular products 

make fiscal sense, and unable to support any conclusions with confidence, many otherwise costeffective (and energy-efficient) projects remain unimplemented.

The TPEx is designed to provide a mechanism through which data providers and data 

consumers can interact. It uses a modular structure, a series of carefully constructed user 

workflows, an open and transparent set of processes, and a robust API to improve the 

identification, storage, and sharing of foundational energy performance data across a range of 

building technologies. Translation of TPEx data into EnergyPlus syntax, and storage of these 

code snippets on the BCL provide significant resource and confidence benefits to the energy 

modeling community as a whole.

Acting as a freely accessible public repository and clearinghouse for product-specific 

energy performance data, the TPEx enables stakeholders to find, leverage, and share data in 

ways not formerly possible, opening new collaboration pathways, and enabling them to conduct 

more effective financial analyses and make better-informed procurement decisions.

Acknowledgements

The NREL Buildings and Thermal Systems Center prepared this document for DOE in 

support of the Technology Performance Exchange project. This project is funded cooperatively 
14

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

by DOE’s Building Technologies Office, DOE’s Federal Energy Management Program, and 

BPA. The authors thank Amy Jiron, Shawn Herrera, David Catarious, Nicolas Baker, and Jason 

Koman (formerly) at DOE, and Tyler Dillavou at BPA for their dedicated support of this project.

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