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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
2 Resources
0 Stars
In progress
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
Publicly accessible
13 Resources
0 Stars
Publicly accessible
WIND Toolkit Long-Term Ensemble Dataset
WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indica...
Wang, J. et al National Renewable Energy Laboratory (NREL)
Jan 24, 2024
7 Resources
1 Stars
Publicly accessible
7 Resources
1 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
Publicly accessible
11 Resources
0 Stars
Publicly accessible
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
14 Resources
1 Stars
Publicly accessible
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
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
14 Resources
0 Stars
Publicly accessible
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
Publicly accessible
4 Resources
0 Stars
Publicly accessible