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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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Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...

Moraga, J. Colorado School of Mines

Apr 27, 2021
11 Resources
0 Stars
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2023 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2023 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

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

Jun 09, 2023
13 Resources
0 Stars
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REopt Lite Geothermal Heat Pump Design Requirements

This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...

Olis, D. National Renewable Energy Laboratory

Mar 08, 2021
4 Resources
0 Stars
Publicly accessible

2021 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

Starting in 2015 NREL has presented the Annual Technology Baseline (ATB) in an Excel workbook that contains detailed cost and performance data, both current and projected, for renewable and conventional technologies. The workbook includes a spreadsheet for each technology. This ve...

Vimmerstedt, L. et al National Renewable Energy Laboratory (NREL)

Jul 12, 2021
11 Resources
0 Stars
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2024 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2024 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

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

Jun 24, 2024
14 Resources
1 Stars
Publicly accessible

Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)

This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api a...

Hale, E. et al National Renewable Energy Laboratory

Jul 08, 2018
6 Resources
0 Stars
Publicly accessible

2022 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2022 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

Vimmerstedt, L. et al National Renewable Energy Laboratory (NREL)

Jun 01, 2022
14 Resources
0 Stars
Publicly accessible

TEAMER: Numerical Model of IProTech PIP WEC Device

iProTech PIP wave energy converter (WEC) is a slack moored, single hull device with no moving parts in the water, joints or bearings. This submission includes data of the simulation, reports, and code for the iProTech PIP (WEC) project. The organization of the data included in the...

Ogden, D. et al IProTech

Nov 02, 2021
2 Resources
0 Stars
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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 Laboratory (NREL)

Jul 16, 2024
6 Resources
0 Stars
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TEAMER: OSU X Hinsdale & Sandia LUPA Uncertainty Testing

This processed data is from TEAMER testing through RFTS 7 at the O.H. Hinsdale Wave Research Laboratory in Corvallis, Oregon. This testing was conducted by Oregon State University (OSU) and Sandia National Laboratories in October and November 2023. The Laboratory Upgrade Point Abs...

Robertson, B. et al Oregon State University

Oct 19, 2023
6 Resources
0 Stars
Publicly accessible

Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling

This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for fiv...

Pauling, H. et al National Renewable Energy Laboratory

Mar 21, 2024
21 Resources
0 Stars
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High Resolution Ocean Surface Wave Hindcast (US Wave) Data

The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project de...

Yang, Z. et al National Renewable Energy Laboratory

Jul 01, 2020
6 Resources
0 Stars
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Imperial Valley Dark Fiber Project Continuous DAS Data

The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...

Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory

Nov 10, 2020
4 Resources
0 Stars
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
4 Resources
0 Stars
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Highly-resolved, Long-term Energy Demand Projections for the Contiguous United States: Data Compiled Using the Demand-side Grid (dsgrid) Toolkit for the Integrated Energy Futures Project

Modeled and compiled datasets describing electricity use by sector, and end use that are geographically specific, hourly, and projected out to 2050 for a single scenario. The current datasets reflect a scenario with a high degree of end-use electrification moderated by high assume...

Hale, E. et al National Renewable Energy Laboratory (NREL)

Feb 04, 2025
2 Resources
0 Stars
In progress

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
Publicly accessible

TEAMER: Tidal Energy Resource Characterization and Model Validation via the Assessment of Distributed Current Measurements from microFloat Swarms, Data and Post-Access Report

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for pro...

Harrison, T. et al University of Washington (NNMREC) Applied Physics Lab

Aug 20, 2020
20 Resources
0 Stars
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PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data

This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...

Feigl, K. et al University of Wisconsin

Mar 29, 2016
20 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
Publicly accessible

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