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Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Admin...

Buster, G. et al National Renewable Energy Lab (NREL)

Oct 15, 2024
7 Resources
0 Stars
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Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets

Wind turbine condition monitoring (CM) can potentially help the wind industry reduce turbine downtime and operation and maintenance (O&M) cost. NREL CM research has investigated various condition-monitoring techniques such as acoustic emission (AE specifically stress wave), vibrat...

Sheng, S. National Renewable Energy Laboratory

Mar 28, 2014
5 Resources
2 Stars
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Wind Integration National Dataset (WIND) Toolkit

Wind resource data for North America was produced using the Weather Research and Forecasting Model (WRF). The WRF model was initialized with the European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-Interm) data set with an initial grid spacing of 54 km. Thre...

Maclaurin, G. et al National Renewable Energy Laboratory

Sep 26, 2014
6 Resources
1 Stars
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Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled ...

Buster, G. et al National Renewable Energy Laboratory (NREL)

Apr 19, 2023
7 Resources
2 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal ...

A., T. Lawrence Livermore National Laboratory

Jan 01, 2012
8 Resources
0 Stars
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Version 2 Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Cook Inlet, AK, 2021

Version 2 of MHKDR submission #475, which also contains the metadata for these measurements. Files here are stored in netCDF4 format, which can be read in Python using the "netcdf4" or "xarray" packages or in MATLAB using the "ncread()" function. Changes are as follows: MWM1 (mi...

Kilcher, L. and McVey, J. Pacific Northwest National Laboratory

Jul 01, 2021
9 Resources
0 Stars
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In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A t...

Bharath, A. et al National Renewable Energy Laboratory

Dec 16, 2022
17 Resources
0 Stars
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2017 Western Passage Tidal Energy Resource Characterization Measurements

These data are from tidal resource characterization measurements collected between April and July 2017 in Western Passage near Eastport, Maine, USA. The dataset contains the following four sub-datasets, each of which is described in more detail in the README.pdf. 1. A bottom-mou...

Kilcher, L. et al National Renewable Energy Laboratory

Jul 31, 2017
33 Resources
0 Stars
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UNH TDP Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary

This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time f...

Wosnik, M. et al National Renewable Energy Laboratory

Dec 21, 2021
30 Resources
0 Stars
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Tidal Energy Resource Characterization, Bottom Lander Measurements, Cook Inlet, AK, 2021

These datasets are from tidal resource characterization measurements collected on the Terrasond High Energy Oceanographic Mooring (THEOM) from 1 July 2021 to 30 August 2021 (60 days) in Cook Inlet, Alaska. The lander was deployed at 60.7207031 N, 151.4294998 W in ~50 m of water. ...

Kilcher, L. and McVey, J. National Renewable Energy Laboratory

Jul 01, 2021
25 Resources
0 Stars
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Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Processed Data, Cook Inlet, AK, 2021

This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Ener...

McVey, J. and Kilcher, L. Pacific Northwest National Laboratory

Aug 31, 2021
28 Resources
0 Stars
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Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the...

Smith, J. Cornell University

Oct 29, 2019
6 Resources
0 Stars
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ARPA-E Grid Optimization (GO) Competition Challenge 2

The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and l...

Elbert, S. et al Pacific Northwest National Laboratory

Sep 20, 2024
29 Resources
0 Stars
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ARPA-E Grid Optimization (GO) Competition Challenge 1

The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each da...