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Sodar NREL Scintec MFAS Wind Profiler, Decker Ranch Airstrip Reviewed Data
**Overview**
The dataset includes 15-minute average wind speed and direction records from 30 m to 330 m above ground level (AGL) in 10-m range gates. Data were collected by a Scintec MFAS wind profiler installed at the Decker Ranch in Oregon, about 4.4 km southeast of Kent, Ore.,...
Jager, D. and Scott, G. Wind Energy Technologies Office (WETO)
Nov 19, 2015
1 Resources
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1 Resources
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Locations of water supplies serving Nairobi, Kenya.
This dataset portrays locations of water supplies serving Nairobi, Kenya. This data was used in Map 3.9 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Locations of dams were approximately located by WRI based on the citations listed below.
"Nature’s...
S, L. National Renewable Energy Laboratory
Dec 27, 2018
2 Resources
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In curation
2 Resources
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In curation
Radar 449MHz Astoria, OR (AST) Reviewed Data
**Overview**
**Winds.**
A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities...
Gottas, D. Wind Energy Technologies Office (WETO)
Sep 02, 2015
1 Resources
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1 Resources
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Radar 449MHz Forks, WA (FKS) Reviewed Data
**Overview**
**Winds.**
A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities...
Gottas, D. Wind Energy Technologies Office (WETO)
Jul 23, 2015
1 Resources
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1 Resources
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Radar 449MHz North Bend, OR (OTH) Raw Data
**Overview**
**Winds.**
A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities...
Gottas, D. Wind Energy Technologies Office (WETO)
Oct 14, 2015
1 Resources
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Publicly accessible
1 Resources
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Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...
Reinisch, E. University of Wisconsin
Jul 28, 2016
1 Resources
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1 Resources
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Utah FORGE: Southwestern Utah Magnetotelluric (MT) Data
This comprehensive magnetotellurics (MT) dataset, which covers southwestern Utah, integrates 600 sites from various surveys, including those from the Utah FORGE, SubTER, and Play Fairway projects, all of which are linked below. The core of this dataset is the use of a 3D finite el...
Wannamaker, P. and Marris, V. Energy and Geoscience Institute at the University of Utah
Jan 22, 2024
4 Resources
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Publicly accessible
4 Resources
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Sodar NREL Scintex SFAS Wind Profiler, Condon Raw Data
**Overview**
The dataset includes 15-minute average wind speed and direction records from 10 m to 250 m above ground level (AGL) in 5-m range gates. Data were collected by a Scintec SFAS wind profiler installed at the Condon State Airport in Oregon, about 1.8 km northeast of the ...
Scott, G. and Jager, D. Wind Energy Technologies Office (WETO)
Nov 19, 2015
1 Resources
0 Stars
Publicly accessible
1 Resources
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Sodar NREL Scintex SFAS Wind Profiler, Condon Reviewed Data
**Overview**
The dataset includes 15-minute average wind speed and direction records from 10 m to 250 m above ground level (AGL) in 5-m range gates. Data were collected by a Scintec SFAS wind profiler installed at the Condon State Airport in Oregon, about 1.8 km northeast of the ...
Scott, G. and Jager, D. Wind Energy Technologies Office (WETO)
Nov 19, 2015
1 Resources
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1 Resources
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BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset
The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...
Tripp, C. et al National Renewable Energy Laboratory
Dec 30, 2022
9 Resources
1 Stars
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9 Resources
1 Stars
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FOSWEC v2: System identification and control testing at Hinsdale Wave Research Laboratory
This report summarizes the design and execution of a wave tank test of the floating oscillating surge wave energy converter (FOSWEC) in the O.H. Hinsdale Wave Research Laboratory Directional Wave Basin at Oregon State University. This device, which uses two "flaps" that pivot abou...
Coe, R. et al Sandia National Laboratories
Feb 01, 2020
2 Resources
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2 Resources
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Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling
This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture.
The wave pump device was deployed off the coast ...
Kimball, C. et al University of New Hampshire, Atlantic Marine Energy Center (AMEC)
Mar 21, 2023
3 Resources
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3 Resources
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Competing Use Analysis for Offshore Renewables and Subsea Cables
Demand for abundant and diverse resources in the oceans is growing, necessitating marine spatial planning. To inform development of Marine Hydrokinetic (MHK) and Offshore Wind (OSW) resources, the Department of Energy (DOE) has asked NREL to identify the competing uses areas betwe...
Best, B. and Kilcher, L. National Renewable Energy Laboratory
Aug 29, 2019
3 Resources
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3 Resources
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Geothermal Water Use: Life Cycle Water Consumption, Water Resource Assessment, and Water Policy Framework
This report examines life cycle water consumption for various geothermal technologies to better understand factors that affect water consumption across the life cycle (e.g., power plant cooling, belowground fluid losses) and to assess the potential water challenges that future geo...
Schroeder, J. et al Argonne National Laboratory
Jun 10, 2014
8 Resources
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8 Resources
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New York State Energy Research and Development Authority Exterior Building Solutions To Insulation
TO4 8.2.2: Space Cond. for Deep Energy Retrofits
The purpose of this project for the New York State Energy Research and Development Authority (NYSERDA) is to find new or improved strategies for exterior building solutions in regard to insulation that will provide extensive energy...
Beach, R. et al Ibacos Innovation
Apr 27, 2016
14 Resources
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14 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
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1 Resources
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NREL Price Series Developed for the ARPA-E FLECCS Program
The price data for four regions (CAISO, ERCOT, MISO-W, and PJM-W) are developed using the ReEDS to PLEXOS conversion as described in (Gagnon et al. 2020). The reference ReEDS case chosen is based on the 2020 Standard Scenario Mid-case, which uses the 2020 ReEDS model version (Cole...
Cohen and DurvasuluNational Renewable Energy Laboratory
Dec 23, 2021
2 Resources
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2 Resources
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Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32
Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, f...
DeWolf, S. and Murdoch, L. Clemson University
Sep 15, 2022
8 Resources
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8 Resources
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Sodar Vaisala Triton Wind Profiler, AON1 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON3 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON5 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON9 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Nov 14, 2016
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON2 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON4 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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Sodar Vaisala Triton Wind Profiler, AON6 Reviewed Data
**Overview**
This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...
Stoelinga, M. Wind Energy Technologies Office (WETO)
Sep 30, 2015
1 Resources
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1 Resources
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