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University of Oregon: GPS-based Precipitable Water Vapor (PWV)
A partnership with the University of Oregon and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect Precipitable Water Vapor (PWV) data to compliment existing resource assessment data collection by the university.
NREL
energy
data
solar energy
wind energy
midc
meteorological
measurement
instrumentation
weather
outdoor
precipitable water vapor
PWV
water column
Oregon
South Park Mountain Data: South Park, Colorado (Data)
South Park, Colorado data including "Live" data and plots, updated every 2 hours.
Daily plots and raw data files, are available from March 28, 1997 to yesterday.
Solar Calendars, are available from March 1997 to the present month.
Wind roses (monthly,…
midc
solar
irradiance
meterological
data
measurement
instrumentation
solar calendar
wind rose
display
weather
outdoor
global
temperature
humidity
wind
silicon
South Park
colorado
NREL
energy
renewable energy
RE
Grid Connected Functionality
Dataset demonstrating the potential benefits that residential buildings can provide for frequency regulation services in the electric power grid. In a hardware-in-the-loop (HIL) implementation, simulated homes along with a physical laboratory home are…
NREL
energy
data
frequency regulation
building-to-grid
home energy management
volttron
aggregator
connected appliances
Energy Systems Integration Facility
ESIF
Golden
colorado
electricity
power grid
residential buildings
Residential Loads May 2, 2016
Power measurements for various residential appliances in the System Performance Lab (SPL) in the Energy System Integration Facility (ESIF). This data set was collected as part of a project evaluating a new type of power meter that can reduce the cost of…
NREL
energy
data
residential
appliances
buildings
ESIF
energy management
Energy System Integration Facility
demand response
Air Conditioner
Range
Oven
Dishwasher
Clothes Washer
Clothes Dryer
Lights
Refrigerator
power meter
submetering
Battery inverter experimental data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We…
battery inverter
data analysis
data visualizations
database for artificial intelligence training
database for inverter characterization
database for model validation
artificial intelligence
machine learning
reinforcement learning
tensorflow
pytorch
scikit-learn
PV inverter experimental data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used…
data analysis
data visualizations
database for artificial intelligence training
database for inverter characterization
database for model validation
artificial intelligence
machine learning
reinforcement learning
tensorflow
pytorch
scikit-learn
PV inverter
Split phase inverter data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 8.35 kW off-the-shelf grid following split phase PV inverter in the…
split phase inverter
PV inverter
data analysis
data visualizations
database for artificial intelligence training
database for inverter characterization
data base for model validation
artificial intelligence
machine learning
reinforcement learning
tensorflow
pytorch
scikit-learn
PV inverter experimental dataset version 2 with 100 percent power
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used…
data analysis
data visualizations
database for artificial intelligence training
database for inverter characterization
database for model validation
artificial intelligence
machine learning
reinforcement learning
tensorflow
pytorch
scikit-learn
PV inverter