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Cited by 1,122

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

U.S. Department of Energy Commercial Reference Building Models of the National Building Stock

Open access
Deru, M., Field, K., Studer, D., Benne, K., Griffith, B., Torcellini, P., Liu, B., Halverson, M., Winiarski, D., Rosenberg, M., Yazdanian, M., Huang, J., Crawley, D.·2011

Abstract

The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

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Registry

Crossref · 10.2172/1009264

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Metadata

Authors
Deru, M., Field, K., Studer, D., Benne, K., Griffith, B., Torcellini, P., Liu, B., Halverson, M., Winiarski, D., Rosenberg, M., Yazdanian, M., Huang, J., & Crawley, D.
Published
2011-02-01
OpenAlex
W2151049413
Cited by
1,122
References
4
Type
report
Language
en
Open access
gold

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CoChat. (2026). Citation check: U.S. Department of Energy Commercial Reference Building Models of the National Building Stock. https://app.cochat.ai/papers/10.2172/1009264
The paper
Deru, M., Field, K., Studer, D., Benne, K., Griffith, B., Torcellini, P., Liu, B., Halverson, M., Winiarski, D., Rosenberg, M., Yazdanian, M., Huang, J., & Crawley, D. (2011). U.S. Department of Energy Commercial Reference Building Models of the National Building Stock. https://doi.org/10.2172/1009264

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.