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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
Publicly accessible

PNNL Distribution System State Estimator Docker Image

This is the docker image for Pacific Northwest National Laboratory's (PNNL) distribution system state estimator (DSSE) used for the demo of OEDI-SI platform. To support the operation of modern distribution systems, operators require real-time visibility into system states. Due to ...

Bhatti, B. et al Pacific Northwest National Laboratory

Jul 10, 2023
6 Resources
2 Stars
Curated

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
Publicly accessible

2023 National Offshore Wind data set (NOW-23)

The 2023 National Offshore Wind data set (NOW-23) is the latest wind resource data set for offshore regions in the United States, which supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published about a decade ago and is curre...

Bodini, N. et al National Renewable Energy Laboratory

Jan 01, 2020
21 Resources
1 Stars
Curated

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

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for we...

Chai, C. et al Oak Ridge National Laboratory

Jun 01, 2020
8 Resources
0 Stars
Publicly accessible

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
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

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

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