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Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States

Publicly accessible License 

Note: This dataset has been superseded by the dataset found at "End-Use Load Profiles for the U.S. Building Stock" (submission 4520; Linked in the submission resources), which is a comprehensive and validated representation of hourly load profiles in the U.S. commercial and residential building stock. The End-Use Load Profiles project website includes links to data viewers for this new dataset. For documentation of dataset validation, model calibration, and uncertainty quantification, see Wilson et al. (2022) (Linked in the submission).

The superseded dataset (Submission #153) was first created around 2012 as a byproduct of various analyses of solar photovoltaics and solar water heating (see references below for are two examples). Because of several errors and limitations present in this dataset, it may be deprecated in the future, once users have had time to transition to the data posted to "End-Use Load Profiles for the U.S. Building Stock".

About this dataset (description updated March 2022):

Weather
The Typical Meteorological Year 3 (TMY3) provides one year of hourly data for around 1,000 locations. The TMY weather represents 30-year normals, which are typical weather conditions over a 30-year period.

Commercial
The commercial load profiles located here are the 16 ASHRAE 90.1-2004 DOE Commercial Prototype Models simulated in all TMY3 locations, with building insulation levels changing based on ASHRAE 90.1-2004 requirements in each climate zone. Within each download, the folder names represent the weather station location of the profiles, whereas the file names represent the building type and the representative city for the ASHRAE climate zone that was used to determine code compliance insulation levels. As indicated by the file names, all building models represent construction that complied with the ASHRAE 90.1-2004 building energy code requirements. No older or newer vintages of buildings are represented.

Residential
The BASE residential load profiles are five EnergyPlus models (one per climate region) representing 2009 IECC construction single-family detached homes simulated in all TMY3 locations. No older or newer vintages of buildings are represented. Each of the five climate regions include only one heating fuel type; electric heating is only found in the Hot-Humid climate. Air conditioning is not found in the Marine climate region.

One major issue with the residential profiles is that for each of the five climate zones, certain location-specific algorithms from one city were applied to entire climate zones. One example is that the heating and cooling operation seasons from each representative city were used across that entire climate zone. For example, in the Hot-Humid files, the heating season calculated for Tampa, FL (December 1 - March 31) was unknowingly applied to all other locations in the Hot-Humid zone, which restricts heating operation outside of those days (for example, heating is disabled in Dallas, TX during cold weather in November). This causes the heating energy to be artificially low in colder parts of that climate zone, and conversely the cooling season restriction leads to artificially low cooling energy use in hotter parts of each climate zone. Additionally, the ground temperatures for the representative city were used across the entire climate zone. This affects water heating energy use (because inlet cold water temperature depends on ground temperature) and heating/cooling energy use (because of ground heat transfer through foundation walls and floors). Representative cities were Tampa, FL (Hot-Humid), El Paso, TX (Mixed-Dry/Hot-Dry), Memphis, TN (Mixed-Humid), Arcata, CA (Marine), and Billings, MT (Cold/Very-Cold).

The residential dataset includes a HIGH building load profile that was intended to provide a rough approximation of older home vintages, but it combines poor thermal insulation with larger house size, tighter thermostat setpoints, and less efficient HVAC equipment. Conversely, the LOW building combines excellent thermal insulation with smaller house size, wider thermostat setpoints, and more efficient HVAC equipment. However, it is not known how well these HIGH and LOW permutations represent the range of energy use in the housing stock.

Downloading
The dataset can be downloaded directly from this submission or from the data index link. Commercial and residential load profile data are accessible as individual files and as downloadable ZIP files. The dataset is approximately 4.8GB compressed or 19GB uncompressed.

Note that on July 2nd, 2013, the Residential High and Low load files were updated from 366 days in a year for leap years to the more general 365 days in a normal year. The archived residential load data is included from prior to this date.

References:
Ong, S., Campbell, C., & Clark, N. (2012). Impacts of regional electricity prices and building type on the economics of commercial photovoltaic systems (No. NREL/TP-6A20-56461). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/56461.pdf

Ong, S., Clark, N., Denholm, P., & Margolis, R. (2013). Breakeven prices for photovoltaics on supermarkets in the United States (No. NREL/TP-6A20-57276). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/57276.pdf

Citation Formats

National Renewable Energy Laboratory. (2014). Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States [data set]. Retrieved from https://dx.doi.org/10.25984/1788456.
Export Citation to RIS
Ong, Sean, Clark, Nathan. Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States. United States: N.p., 25 Nov, 2014. Web. doi: 10.25984/1788456.
Ong, Sean, Clark, Nathan. Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States. United States. https://dx.doi.org/10.25984/1788456
Ong, Sean, Clark, Nathan. 2014. "Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States". United States. https://dx.doi.org/10.25984/1788456. https://data.openei.org/submissions/153.
@div{oedi_153, title = {Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States}, author = {Ong, Sean, Clark, Nathan.}, abstractNote = {Note: This dataset has been superseded by the dataset found at "End-Use Load Profiles for the U.S. Building Stock" (submission 4520; Linked in the submission resources), which is a comprehensive and validated representation of hourly load profiles in the U.S. commercial and residential building stock. The End-Use Load Profiles project website includes links to data viewers for this new dataset. For documentation of dataset validation, model calibration, and uncertainty quantification, see Wilson et al. (2022) (Linked in the submission).

The superseded dataset (Submission #153) was first created around 2012 as a byproduct of various analyses of solar photovoltaics and solar water heating (see references below for are two examples). Because of several errors and limitations present in this dataset, it may be deprecated in the future, once users have had time to transition to the data posted to "End-Use Load Profiles for the U.S. Building Stock".

About this dataset (description updated March 2022):

Weather
The Typical Meteorological Year 3 (TMY3) provides one year of hourly data for around 1,000 locations. The TMY weather represents 30-year normals, which are typical weather conditions over a 30-year period.

Commercial
The commercial load profiles located here are the 16 ASHRAE 90.1-2004 DOE Commercial Prototype Models simulated in all TMY3 locations, with building insulation levels changing based on ASHRAE 90.1-2004 requirements in each climate zone. Within each download, the folder names represent the weather station location of the profiles, whereas the file names represent the building type and the representative city for the ASHRAE climate zone that was used to determine code compliance insulation levels. As indicated by the file names, all building models represent construction that complied with the ASHRAE 90.1-2004 building energy code requirements. No older or newer vintages of buildings are represented.

Residential
The BASE residential load profiles are five EnergyPlus models (one per climate region) representing 2009 IECC construction single-family detached homes simulated in all TMY3 locations. No older or newer vintages of buildings are represented. Each of the five climate regions include only one heating fuel type; electric heating is only found in the Hot-Humid climate. Air conditioning is not found in the Marine climate region.

One major issue with the residential profiles is that for each of the five climate zones, certain location-specific algorithms from one city were applied to entire climate zones. One example is that the heating and cooling operation seasons from each representative city were used across that entire climate zone. For example, in the Hot-Humid files, the heating season calculated for Tampa, FL (December 1 - March 31) was unknowingly applied to all other locations in the Hot-Humid zone, which restricts heating operation outside of those days (for example, heating is disabled in Dallas, TX during cold weather in November). This causes the heating energy to be artificially low in colder parts of that climate zone, and conversely the cooling season restriction leads to artificially low cooling energy use in hotter parts of each climate zone. Additionally, the ground temperatures for the representative city were used across the entire climate zone. This affects water heating energy use (because inlet cold water temperature depends on ground temperature) and heating/cooling energy use (because of ground heat transfer through foundation walls and floors). Representative cities were Tampa, FL (Hot-Humid), El Paso, TX (Mixed-Dry/Hot-Dry), Memphis, TN (Mixed-Humid), Arcata, CA (Marine), and Billings, MT (Cold/Very-Cold).

The residential dataset includes a HIGH building load profile that was intended to provide a rough approximation of older home vintages, but it combines poor thermal insulation with larger house size, tighter thermostat setpoints, and less efficient HVAC equipment. Conversely, the LOW building combines excellent thermal insulation with smaller house size, wider thermostat setpoints, and more efficient HVAC equipment. However, it is not known how well these HIGH and LOW permutations represent the range of energy use in the housing stock.

Downloading
The dataset can be downloaded directly from this submission or from the data index link. Commercial and residential load profile data are accessible as individual files and as downloadable ZIP files. The dataset is approximately 4.8GB compressed or 19GB uncompressed.

Note that on July 2nd, 2013, the Residential High and Low load files were updated from 366 days in a year for leap years to the more general 365 days in a normal year. The archived residential load data is included from prior to this date.

References:
Ong, S., Campbell, C., & Clark, N. (2012). Impacts of regional electricity prices and building type on the economics of commercial photovoltaic systems (No. NREL/TP-6A20-56461). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/56461.pdf

Ong, S., Clark, N., Denholm, P., & Margolis, R. (2013). Breakeven prices for photovoltaics on supermarkets in the United States (No. NREL/TP-6A20-57276). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/57276.pdf }, doi = {10.25984/1788456}, url = {https://data.openei.org/submissions/153}, journal = {}, number = , volume = , place = {United States}, year = {2014}, month = {11}}

The superseded dataset (Submission #153) was first created around 2012 as a byproduct of various analyses of solar photovoltaics and solar water heating (see references below for are two examples). Because of several errors and limitations present in this dataset, it may be deprecated in the future, once users have had time to transition to the data posted to "End-Use Load Profiles for the U.S. Building Stock".

About this dataset (description updated March 2022):

Weather
The Typical Meteorological Year 3 (TMY3) provides one year of hourly data for around 1,000 locations. The TMY weather represents 30-year normals, which are typical weather conditions over a 30-year period.

Commercial
The commercial load profiles located here are the 16 ASHRAE 90.1-2004 DOE Commercial Prototype Models simulated in all TMY3 locations, with building insulation levels changing based on ASHRAE 90.1-2004 requirements in each climate zone. Within each download, the folder names represent the weather station location of the profiles, whereas the file names represent the building type and the representative city for the ASHRAE climate zone that was used to determine code compliance insulation levels. As indicated by the file names, all building models represent construction that complied with the ASHRAE 90.1-2004 building energy code requirements. No older or newer vintages of buildings are represented.

Residential
The BASE residential load profiles are five EnergyPlus models (one per climate region) representing 2009 IECC construction single-family detached homes simulated in all TMY3 locations. No older or newer vintages of buildings are represented. Each of the five climate regions include only one heating fuel type; electric heating is only found in the Hot-Humid climate. Air conditioning is not found in the Marine climate region.

One major issue with the residential profiles is that for each of the five climate zones, certain location-specific algorithms from one city were applied to entire climate zones. One example is that the heating and cooling operation seasons from each representative city were used across that entire climate zone. For example, in the Hot-Humid files, the heating season calculated for Tampa, FL (December 1 - March 31) was unknowingly applied to all other locations in the Hot-Humid zone, which restricts heating operation outside of those days (for example, heating is disabled in Dallas, TX during cold weather in November). This causes the heating energy to be artificially low in colder parts of that climate zone, and conversely the cooling season restriction leads to artificially low cooling energy use in hotter parts of each climate zone. Additionally, the ground temperatures for the representative city were used across the entire climate zone. This affects water heating energy use (because inlet cold water temperature depends on ground temperature) and heating/cooling energy use (because of ground heat transfer through foundation walls and floors). Representative cities were Tampa, FL (Hot-Humid), El Paso, TX (Mixed-Dry/Hot-Dry), Memphis, TN (Mixed-Humid), Arcata, CA (Marine), and Billings, MT (Cold/Very-Cold).

The residential dataset includes a HIGH building load profile that was intended to provide a rough approximation of older home vintages, but it combines poor thermal insulation with larger house size, tighter thermostat setpoints, and less efficient HVAC equipment. Conversely, the LOW building combines excellent thermal insulation with smaller house size, wider thermostat setpoints, and more efficient HVAC equipment. However, it is not known how well these HIGH and LOW permutations represent the range of energy use in the housing stock.

Downloading
The dataset can be downloaded directly from this submission or from the data index link. Commercial and residential load profile data are accessible as individual files and as downloadable ZIP files. The dataset is approximately 4.8GB compressed or 19GB uncompressed.

Note that on July 2nd, 2013, the Residential High and Low load files were updated from 366 days in a year for leap years to the more general 365 days in a normal year. The archived residential load data is included from prior to this date.

References:
Ong, S., Campbell, C., & Clark, N. (2012). Impacts of regional electricity prices and building type on the economics of commercial photovoltaic systems (No. NREL/TP-6A20-56461). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/56461.pdf

Ong, S., Clark, N., Denholm, P., & Margolis, R. (2013). Breakeven prices for photovoltaics on supermarkets in the United States (No. NREL/TP-6A20-57276). National Renewable Energy Lab.(NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy13osti/57276.pdf }, doi = {10.25984/1788456}, url = {https://data.openei.org/submissions/153}, journal = {}, number = , volume = , place = {United States}, year = {2014}, month = {11}}" readonly />
https://dx.doi.org/10.25984/1788456

Details

Data from Nov 25, 2014

Last updated Mar 16, 2022

Submitted Nov 25, 2014

Organization

National Renewable Energy Laboratory

Contact

Eric Wilson

Authors

Sean Ong

National Renewable Energy Laboratory

Nathan Clark

National Renewable Energy Laboratory

Research Areas

DOE Project Details

Project Name Hourly Load Profiles of Commercial and Residential Buildings

Project Number EE0042015

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