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Oil and Gas Basins in Alaska

Oil and gas basins in Alaska, available as GIS shape files. Digitized by Alaska Department of Natural Resources (ADNR), Information Resource Management Section. Digitized from DGGS publication, Special Report 32, Oil and Gas Basins Map of Alaska 1983, by Arlen Ehm. ### License ...

Hallett, K. and (AEDI), A. National Renewable Energy Laboratory

Dec 30, 1983
2 Resources
0 Stars
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Next Generation RivGen Power System: Feasibility Assessment of Hydroacoutics Data for Development of a Probability of Encounter Model of Salmon Smolts

This document contains a feasibility assessment for salmon smolt characterization and analysis based on existing hydroacoustics data and probability of encounter model.

Daroux, A. and Zydlewski, G. Igiugig Village Council

Oct 04, 2017
1 Resources
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Sustainable Federal Fleets

This data reveals trends in Federal agencies' alternative fuel vehicle acquisitions, petroleum-reduction efforts, and alternative fuel use. This data can help agencies analyze their fleets' performance in meeting Federal mandates.

Reichhardt, M. and (EERE), O. Office of Energy Efficiency & Renewable Energy

Nov 25, 2014
1 Resources
0 Stars
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Electric Power Monthly Monthly Data Tables

U.S. monthly electricity generation figures from 2008 to 2010 (and the fuel consumed to produce it) by state. Original source information from the [U.S. Energy Information Administration (EIA)](http://www.eia.doe.gov/cneaf/electricity/epa/epa_sprdshts_monthly.html).

Wood, J. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
3 Resources
0 Stars
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Microwave Radiometer CU Radiometrics MWR, Condon Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
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Microwave Radiometer CU Radiometrics MWR, Condon Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
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Microwave Radiometer ESRL Radiometrics MWR, Troutdale Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
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Microwave Radiometer ESRL Radiometrics MWR, Troutdale Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
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Microwave Radiometer ESRL Radiometrics MWR, Wasco Airport Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
Publicly accessible

Microwave Radiometer ESRL Radiometrics MWR, Wasco Airport Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
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Microwave Radiometer UND Radiometrics MWR, Rufus Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
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PV Rooftop Database for Puerto Rico (PVRDB-PR)

The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded a...

Mooney, M. and Waechter, K. National Renewable Energy Laboratory (NREL)

Dec 16, 2020
5 Resources
0 Stars
Curated

North and South Dakota High Resolution 50m Wind Resource

Annual average wind resource potential for North and South Dakota at a 50 meter height in a GIS shapefile and links to US national wind resource information tools. This data set was produced and validated by NREL using their WRAM model.

Langle, N. and Lopez, A. National Renewable Energy Laboratory

Nov 25, 2014
4 Resources
0 Stars
Curated

United States Utility-Scale PV Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for utility-scale PV across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCO...

GDS, N. National Renewable Energy Laboratory

Jun 30, 2023
13 Resources
1 Stars
Curated

wfip2.model/retro.hrrr.01.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
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wfip2.model/retro.hrrr.01.fcst.02

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.02.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.02.fcst.02

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.rap.01.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.rap.02.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Feb 09, 2016
1 Resources
0 Stars
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Wave Energy Prize 1/50th Testing M3 Wave Submerged Mid-Column Pressure Differential WEC

This submission of data includes all the 1/50th scale testing data completed on the Wave Energy Prize for the M3 Wave team, and includes: 1/50th test data (raw & processed) 1/50th test data video and pictures 1/50th Test plans and testing documents SSTF_Submission (summarized ...

Scharmen, W. Ricardo Detroit Technical Center

Jan 08, 2016
10 Resources
0 Stars
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Distributed Generation Market Demand (dGen) model

The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sector...

Stanley, T. et al National Renewable Energy Laboratory (NREL)

Oct 16, 2020
4 Resources
0 Stars
Curated

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transpor...

Yip, A. et al National Renewable Energy Laboratory

Aug 29, 2023
8 Resources
0 Stars
Curated

Miller & Keith (2018) Wind Plant Data

Information on the 430 wind power plants used in 'Observation-based solar and wind power capacity factors and power densities’ by Miller & Keith (2018, Environ. Res. Lett. 13 104008), initially based on the Wind Power Plant locations released by the US Energy Information Adminis...

Miller, L. Harvard University

Nov 22, 2018
2 Resources
0 Stars
In curation

Friends Center Building, Philadelphia, Pennsylvania

The data from the Friends Center Building in Philadelphia, Pennsylvania, come from a one-year study of 24 U.S. office occupants. These office occupants recorded a set of possible drivers of personal comfort and behavior over time by completing online daily surveys, which provided ...

Langevin, J. and Luo, N. Building Technologies Office (BTO)

Feb 22, 2022
1 Resources
0 Stars
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