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United States Land-based Wind Supply Curves 2024

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...

Geospatial Data Science, N. National Renewable Energy Laboratory

Jan 01, 2025
12 Resources
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United States Utility-Scale PV Supply Curves 2024

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...

Geospatial Data Science, N. National Renewable Energy Laboratory

Jan 01, 2025
12 Resources
0 Stars
Publicly accessible

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corpo...

Obika, K. et al National Renewable Energy Laboratory

Nov 05, 2025
2 Resources
0 Stars
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Demand-Side Grid (dsgrid) Building Load Profiles using ResStock and ComStock v2021

This dataset contains simulated hourly end use load profiles of the residential and commercial building sector in the contiguous United States for every other year from 2010 to 2050. Data were produced in 2021 using ResStock and ComStock, which are building stock energy models of ...

Liu, L. et al National Renewable Energy Lab (NREL)

Apr 12, 2021
9 Resources
1 Stars
Publicly accessible

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting

The BuildingsBench datasets consist of: Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock. 7 real residential and com...

Emami, P. and Graf, P. National Renewable Energy Laboratory

Dec 31, 2018
6 Resources
1 Stars
Publicly accessible

SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS

The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the data...

Palmintier, B. et al National Renewable Energy Laboratory (NREL)

Dec 18, 2020
5 Resources
1 Stars
Publicly accessible

Hourly Dynamic Line Ratings for Existing Transmission Across the Contiguous United States (Preliminary)

This dataset provides estimated hourly dynamic line ratings for ~84,000 transmission lines across the contiguous United States from 2007-2013. The calculation methods are described in the presentation linked below, and the associated open-source Python code repository is linked in...

Obika, K. et al National Renewable Energy Laboratory

Sep 25, 2024
16 Resources
0 Stars
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PV Module Standoff and T98 Safety Maps for the United States (IEC 61730, 70 & 80 Celsius)

This dataset provides high-resolution maps of modeled photovoltaic (PV) module standoff distance and associated thermal conditions across the United States for two thermal design scenarios (T98 = 70 degrees C and 80 degrees C), representing distinct module temperature limits used ...

Springer, M. et al National Laboratory of the Rockies (NLR)

Apr 13, 2026
3 Resources
0 Stars
Awaiting curation

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI) as well as other meteorological dat...

Yang, J. et al National Renewable Energy Laboratory (NREL)

Sep 30, 2024
5 Resources
0 Stars
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
6 Resources
0 Stars
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AlphaBuilding Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with...

Li, H. et al Lawrence Berkeley National Laboratory

Dec 21, 2020
5 Resources
0 Stars
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National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information t...

Sengupta, M. et al National Renewable Energy Laboratory

Sep 28, 2018
7 Resources
2 Stars
Publicly accessible

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
2 Stars
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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
6 Resources
0 Stars
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