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Turbine Depth Optimization Study, Admiralty Inlet, WA
The zipped file contains a directory of data and routines used in the NNMREC turbine depth optimization study (Kawase et al., 2011), and calculation results thereof. For further info, please contact Mitsuhiro Kawase at kawase@uw.edu.
Kawase, M. et al University of Washington
Nov 22, 2009
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Buster, G. et al Upflow
Jun 30, 2021
11 Resources
0 Stars
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11 Resources
0 Stars
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StingRAY Structural Optimization Final Technical Report
The overall project objective is to materially decrease the leveled cost of energy (LCOE) of the Columbia Power (CPower) StingRAY utility-scale wave energy converter (WEC). This will be achieved by reducing structural material and manufacturing costs and increasing energy output. ...
Lenee-Bluhm, P. Columbia Power Technologies, Inc.
Aug 05, 2020
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
GeoRePORT Input Spreadsheet
The Geothermal Resource Portfolio Optimization and Reporting Tool (GeoRePORT) was developed as a way to distill large amounts of geothermal project data into an objective, reportable data set that can be used to communicate with experts and non-experts. GeoRePORT summarizes (1) r...
St. Onge, M. National Renewable Energy Laboratory
Apr 27, 2017
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
6 Resources
0 Stars
Publicly accessible
6 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
ARPA-E Grid Optimization (GO) Competition Challenge 2
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and l...
Elbert, S. et al Pacific Northwest National Laboratory
Sep 20, 2024
29 Resources
0 Stars
Curated
29 Resources
0 Stars
Curated
Ocean Thermal Energy Conversion (OTEC) delta T (Winter Average)
This shapefile represents seasonal winter average delta T estimates.
ΔT represents the difference in temperature (°C) between the warm and cold water sources used by an OTEC plant at a specific location. Warm water is defined uniformly as water at a depth of 20 m, whi...
ΔT represents the difference in temperature (°C) between the warm and cold water sources used by an OTEC plant at a specific location. Warm water is defined uniformly as water at a depth of 20 m, whi...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
ARPA-E Grid Optimization (GO) Competition Challenge 1
The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each da...
Elbert, S. et al Pacific Northwest National Laboratory
Aug 05, 2024
29 Resources
0 Stars
Curated
29 Resources
0 Stars
Curated
Integrated: Geospatial Toolkit GIS data for Bhutan from NREL
The Geospatial Toolkit (GsT) is a map viewer developed by the National Renewable Energy Laboratory (NREL). The toolkit helps energy planners, project developers, researchers and others identify areas of a country that show good potential for renewable energy projects. The toolkit ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Integrated: Geospatial Toolkit GIS data for India from NREL
The Geospatial Toolkit (GsT) is a map viewer developed by the National Renewable Energy Laboratory (NREL). The toolkit helps energy planners, project developers, researchers and others identify areas of a country that show good potential for renewable energy projects. The toolkit ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Integrated: Geospatial Toolkit GIS data for Oaxaca from NREL
The Geospatial Toolkit (GsT) is a map viewer developed by the National Renewable Energy Laboratory (NREL). The toolkit helps energy planners, project developers, researchers and others identify areas of a country that show good potential for renewable energy projects. The toolkit ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets
This dataset contains turbine and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in ...
Ramos, D. et al National Renewable Energy Laboratory
Feb 12, 2021
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 3
Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public.
The Grid Optimizat...
Elbert, S. et al Pacific Northwest National Laboratory
May 02, 2024
39 Resources
1 Stars
Curated
39 Resources
1 Stars
Curated
Error-Level-Controlled Synthetic Forecasts for Renewable Generation
Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...
Zhang, X. et al National Renewable Energy Laboratory (NREL)
Jun 01, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Ocean Thermal Energy Conversion (OTEC) Cold Water Depth (Annual Average)
This shapefile represents annual average cold water depth recordings.
The cold water is defined by locating the depth that leads to the greatest average annual net power at each location when depth and its corresponding ?T are input into the power equation. This optimization ba...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) Cold Water Depth (Summer Average)
This shapefile represents seasonal summer average cold water depth recordings.
The cold water is defined by locating the depth that leads to the greatest average annual net power at each location when depth and its corresponding ΔT are input into the power equation. This optim...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) Cold Water Depth (Winter Average)
This shapefile represents seasonal winter average cold water depth recordings.
The cold water is defined by locating the depth that leads to the greatest average annual net power at each location when depth and its corresponding ΔT are input into the power equation. This optim...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) delta T (Annual Average)
This shapefile represents annual average delta T estimates.
ΔT represents the difference in temperature (°C) between the warm and cold water sources used by an OTEC plant at a specific location. Warm water is defined uniformly as water at a depth of 20 m, while cold water is ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) delta T (Summer Average)
This shapefile represents seasonal summer average delta T estimates.
ΔT represents the difference in temperature (°C) between the warm and cold water sources used by an OTEC plant at a specific location. Warm water is defined uniformly as water at a depth of 20 m, while cold ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
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
Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems
Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduct...
Hu, J. et al Lawrence Berkeley National Laboratory
Jan 31, 2022
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible