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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
15 Resources
0 Stars
Curated
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
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
13 Resources
1 Stars
Curated
The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017
The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a uni...
McMillan, C. et al National Renewable Energy Laboratory (NREL)
Jul 01, 2024
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
Utah FORGE Phase Native State FALCON Model Files
The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...
Podgorney, R. Idaho National Laboratory
Jun 06, 2019
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
7 Resources
0 Stars
Publicly accessible
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
6 Resources
0 Stars
Publicly accessible
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
Publicly accessible
6 Resources
0 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
Modeling the Integration of Marine Energy into Microgrids Wave Resource Assessment
This submission has wave resource assessments which were conducted for six locations based on IEC requirements using the DOE WPTO Hindcast data and MHKiT. The locations are chosen to provide varying wave climates and include PacWave South, OR; Wave Energy Testing Site (WETS), HI; ...
Mankle, H. and Robertson, B. University of Alaska Fairbanks
Jan 19, 2023
9 Resources
0 Stars
Publicly accessible
9 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