U.S. Department of EnergyOffice of Scientific and Technical Information
NREL RSF Weather Data 2011
Abstract
Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Weather data form the RSF systems energy model. The weather data was used to contextualize and compare energy use data like heating and cooling. The weather data was also used by the RSF Energy Model to model the energy use of the RSF. Energy Model data and Measured Energy data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.
- Authors:
-
- National Renewable Energy Laboratory
- Publication Date:
- Other Number(s):
- 359
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); National Renewable Energy Laboratory
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office (EE-5B)
- Collaborations:
- National Renewable Energy Laboratory
- Subject:
- 2011; Array; Colorado; Golden; NREL; RSF; Research Support Facility; building energy; building systems; buildings; consumption; control strategy; data; energy analysis; energy conservation; energy modeling; model; usage; utilization; weather
- OSTI Identifier:
- 1845287
- DOI:
- https://doi.org/10.25984/1845287
Citation Formats
Sheppy, Michael, Beach, Aaron, and Pless, Shanti. NREL RSF Weather Data 2011. United States: N. p., 2014.
Web. doi:10.25984/1845287.
Sheppy, Michael, Beach, Aaron, & Pless, Shanti. NREL RSF Weather Data 2011. United States. doi:https://doi.org/10.25984/1845287
Sheppy, Michael, Beach, Aaron, and Pless, Shanti. 2014.
"NREL RSF Weather Data 2011". United States. doi:https://doi.org/10.25984/1845287. https://www.osti.gov/servlets/purl/1845287. Pub date:Mon Nov 24 23:00:00 EST 2014
@article{osti_1845287,
title = {NREL RSF Weather Data 2011},
author = {Sheppy, Michael and Beach, Aaron and Pless, Shanti},
abstractNote = {Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Weather data form the RSF systems energy model. The weather data was used to contextualize and compare energy use data like heating and cooling. The weather data was also used by the RSF Energy Model to model the energy use of the RSF. Energy Model data and Measured Energy data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.},
doi = {10.25984/1845287},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 24 23:00:00 EST 2014},
month = {Mon Nov 24 23:00:00 EST 2014}
}