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United States Land-based Wind Supply Curves 2023

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

GDS, N. National Renewable Energy Laboratory

Jun 30, 2023
13 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

United States Offshore Wind Supply Curves 2024

This data packet contains supply curves, hourly generation profiles, and composite siting exclusion TIFFs for offshore wind (OSW) in the waters of the EEZ off the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), level...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jan 01, 2024
15 Resources
0 Stars
Curated

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and hi...

Speake, A. et al National Renewable Energy Lab

Mar 03, 2023
6 Resources
0 Stars
Curated

Bias Corrected HRRR Wind Resource Data for Grid Integration Applications

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's G...

Pinchuk, P. et al The National Renewable Energy Lab (NREL)

Oct 15, 2024
4 Resources
0 Stars
In progress

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 The National Renewable Energy Lab (NREL)

Apr 19, 2023
7 Resources
1 Stars
Curated

Sup3rWind Data (CONUS)

This data contains paired European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit (WTK) images for 2007 and 2010 over two regions in the US, with domain sizes ~800x800 (latitudes from 25.89 to 41.58, and long...

Sinha, S. et al National Renewable Energy Lab NREL

Jul 16, 2024
6 Resources
0 Stars
Curated

Early Market Opportunity MHK Energy Site Identification Wave and Tidal Resources

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--base...

Kilcher, L. National Renewable Energy Laboratory

Apr 01, 2016
7 Resources
0 Stars
Publicly accessible

Demand-Side Grid (dsgrid) Highly-resolved, Long-term Energy Demand Projections for the Contiguous United States: DECARB Scenarios

Input and compiled datasets describing projected energy use by sector and for the power sector as a whole. Data are developed by a multi-national lab team as part of the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Office's DECARB project.

Hale, E. et al National Renewable Energy Laboratory

Jul 01, 2024
2 Resources
0 Stars
In progress

BUTTER Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...

Tripp, C. et al National Renewable Energy Laboratory

May 20, 2022
4 Resources
0 Stars
Publicly accessible

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
Curated

G2Aero Database of Airfoils Curated Airfoils

This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes. We constructed the a...

Doronina, O. et al National Renewable Energy Lab NREL

Sep 24, 2024
3 Resources
0 Stars
Curated