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Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)
The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios.
Sup3rCC is downscaled ...
Buster, G. et al The National Renewable Energy Lab (NREL)
Apr 19, 2023
7 Resources
1 Stars
Publicly accessible
7 Resources
1 Stars
Publicly accessible
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
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2013)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Jul 13, 2015
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
dsgrid-TEMPO light-duty vehicle charging profiles v2022
Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data produced in 2022 using the Transportati...
Yip, A. et al National Renewable Energy Laboratory
Aug 29, 2023
4 Resources
0 Stars
In progress
4 Resources
0 Stars
In progress
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal energy production. Phase 1 includes reservoir analyses to determine injector/producer well schemes that balance the generation of economically useful flow rates at the ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (Feb 2011)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
5 Resources
0 Stars
Publicly accessible
5 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
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
Publicly accessible
6 Resources
2 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
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2014)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Dec 01, 2015
7 Resources
0 Stars
Publicly accessible
7 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
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2020)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. National Renewable Energy Laboratory (NREL)
Dec 01, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2021)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. National Renewable Energy Laboratory (NREL)
Nov 21, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2022)
This dataset, compiled by NREL using data from ABB, the Velocity Suite (http://energymarketintel.com/) and the U.S. Energy Information Administration dataset 861 (http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity rate...
Huggins, J. National Renewable Energy Laboratory (NREL)
Apr 05, 2024
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2017)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Oct 24, 2018
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2018)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Oct 25, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2019)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. National Renewable Energy Laboratory (NREL)
Dec 01, 2020
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Catalyst Design in Nitrate Removal
Based on the volcano plot developed by Dr. Goldsmith group (Report linked in submission), we utilized DFT (density functional theory) calculations to search for bimetallic materials in the application of catalysts in aqueous nitrate removal. The calculations are conducted via the ...
Wang, D. and Jain, A. Lawrence Berkeley National Laboratory
Dec 01, 2021
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Combined Heat and Power Installation Database
The Combined Heat & Power (CHP) Installation Database contains information about all the known CHP installations across the country. This data is compiled through a variety of sources and is the only known data set of its kind. DOE, in partnership with the Oak Ridge National Labor...
Hampson, A. and Laboratory, O. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
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
Publicly accessible
4 Resources
0 Stars
Publicly accessible
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
Bouira University Digital Space
Description archive of our university and/or Remarks:
The University of Bouira offers visitors from Bouira University Digital Space a free downloadable files (memories doctoral, master, master, courses in different technological and literary disciplines, proceedings of scientif...
Chettabi, . National Renewable Energy Laboratory
Jan 08, 2000
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy
This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the...
Smith, J. Cornell University
Oct 29, 2019
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Wind and Structural Loads on Parabolic Trough Solar Collectors at Nevada Solar One
Wind loading is a main contributor to structural design costs of Concentrating Solar Power (CSP) collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind. At the same time, the reflector surfaces must exhi...
Egerer, U. et al National Renewable Energy Laboratory (NREL)
Oct 01, 2021
4 Resources
0 Stars
Publicly accessible
4 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