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Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging Software and Data

Software and testing data from the OH Hinsdale Wave lab for DOE-funded project on Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging. This project will perform foundational research and testing to accelerate the sector-wide development a...

Hollinger, G. et al Oregon State University

Oct 26, 2022
11 Resources
0 Stars
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MBARI WEC 2021 deployment

This dataset includes data from the Monterey Bay Aquarium Research Institute (MBARI) wave energy converter (WEC) and a nearby located Sofar Spotter buoy. The Monterey Bay Aquarium Research Institute has developed and deployed a small two-body point absorber wave energy device suit...

Coe, R. et al Sandia National Laboratories

Oct 12, 2021
4 Resources
0 Stars
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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
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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
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MHK Levelized Cost of Energy (LCOE) Guidance and Techno-Economic Analysis Materials

Useful information and tools for calculating the Levelized Cost of Energy (LCOE) and MHK Cost Breakdown Structure. Includes a structure for calculating the capital expenditures and operating costs of a marine energy technology or device, reference resource data for both wave and ...

Jenne, S. and Baca, E. National Renewable Energy Laboratory

Nov 08, 2019
7 Resources
0 Stars
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Admiralty Inlet Hub-Height Turbulence Measurements from June 2012

This data is from measurements at Admiralty Head, in Admiralty Inlet. The measurements were made using an IMU equipped ADV mounted on a mooring, the 'Tidal Turbulence Mooring' or 'TTM'. The inertial measurements from the IMU allows for removal of mooring motion in post processing....

Kilcher, L. National Renewable Energy Laboratory

Jun 18, 2012
7 Resources
0 Stars
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EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility

This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...

Chai, C. et al Lawrence Berkeley National Laboratory

Feb 06, 2019
3 Resources
0 Stars
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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
1 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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NREL Eagle supercomputer jobs

High performance computing dataset with 11M+ jobs from NREL's Eagle supercomputer. These jobs were submitted to run on Eagle between Nov 2018 and Feb 2023. The data are sufficiently anonymized and do not include sensitive user or project data. HPC research community does not have ...

Duplyakin, D. and Menear, K. National Renewable Energy Laboratory

Feb 28, 2023
4 Resources
0 Stars
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Optimization of Marine Energy Conversion Systems Through Modeling, Optimization, and CHIL Validation

The work aims to achieve optimal tidal energy conversion through a comprehensive approach of modeling, optimization, and control hardware-in-the-loop (CHIL) validation. By developing accurate models and employing optimization techniques, it seeks to identify efficient system confi...

Luo, F. et al Stony Brook University

Jul 17, 2023
6 Resources
0 Stars
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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
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Linearized Distribution Optimal Power Flow for OEDI SI

This research is to meant to demonstrate the OEDI SI use case for distributed optimal power flow (DOPF). The goal was to formulate the optimal power flow problem in the distribution system for active and reactive power setpoints of PV systems using topology information and voltage...

Sadnan, R. et al Pacific Northwest National Laboratory

Oct 03, 2023
1 Resources
0 Stars
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HERO WEC V1.0 Electrical PTO Deployment Data and Analysis

This submission includes the processed and raw field electrical data from NREL's August 2022 HERO WEC (hydraulic and electric reverse osmosis wave energy converter) deployment at Jennette's Pier for the electrical PTO (power take-off).

Nakhai, A. et al National Renewable Energy Laboratory

Aug 12, 2022
4 Resources
0 Stars
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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
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ALFA Station Keeping Results for Seabotix vLBV300 Underwater Vehicle near Newport, OR

This data set presents results testing the station keeping abilities of a tethered Seabotix vLBV300 underwater vehicle equipped with an inertial navigation system. These results are from an offshore deployment on April 20, 2016 off the coast of Newport, OR (44.678 degrees N, 124.1...

Hollinger, G. Oregon State University

Apr 20, 2016
8 Resources
0 Stars
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2024 Annual Technology Baseline (ATB) Cost and Performance Data for Transportation Technologies

The 2024 Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates: time-series through 2050 for light, medium, and hea...

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

Nov 11, 2024
5 Resources
0 Stars
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Admiralty Inlet Advanced Turbulence Measurements: May 2015

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in May of 2015. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on a 'StableMoor' (Manufacturer: DeepWater Buoyancy) buoy and a Tidal Turbulence Mooring (TTM). Thes...

Kilcher, L. National Renewable Energy Laboratory

May 18, 2015
18 Resources
0 Stars
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2022 Annual Technology Baseline (ATB) Cost and Performance Data for Transportation Technologies

The 2022 Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates: time-series through 2050 for light, medium, and hea...

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

Nov 17, 2023
5 Resources
0 Stars
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Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging Test Data and Processing

This dataset contains experimental results from testing the Halona wave energy converter (WEC) in both fixed and floating configurations. This dataset reflects a 1/10th scale omnidirectional spar buoy oscillating water column (OWC) device, designed to improve platform stability fo...

Ulm, N. et al University of Hawaii at Manoa

Mar 01, 2021
44 Resources
0 Stars
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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...

Vesselinov, V. Los Alamos National Laboratory

Mar 29, 2021
4 Resources
0 Stars
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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
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HERO WEC Belt Test Data

The following submission includes raw and processed data from the 2024 Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) belt tests conducted using NREL's Large Amplitude Motion Platform (LAMP). A description of the motion profiles run during testing can be f...

Jenne, S. et al National Renewable Energy Laboratory

Sep 01, 2024
7 Resources
0 Stars
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BUTTER Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...

Tripp, C. et al National Renewable Energy Laboratory

May 20, 2022
4 Resources
0 Stars
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BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset

The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...