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An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Geothermal Behavior with Example Simulations on The Treasure Island and UC Berkeley Campus

This submission contains the source code of the Hydrothermal Finite Element Simulator used for the Treasure Island and UC Berkeley campus geothermal simulation. It contains a report that summarizes the development and validation of this Hydrothermal Finite Element Simulator, with ...

Chen, K. et al Lawrence Berkeley National Laboratory

Aug 01, 2021
5 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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1D Heat Loss Models Validation Experiment

Contains data from the model validation in the 1D Heat Loss Models to Predict the Aquifer Temperature Profile during Hot/Cold Water Injection Project. The data include two COMSOL models (2D axisymmetric benchmark model and 2D Vinsome model), one python code (1D Vinsome based FEM n...

Chen, K. et al UC Berkeley

Jan 18, 2022
8 Resources
0 Stars
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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

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
0 Stars
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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
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Bias Corrected HRRR Wind Resource Data for Grid Integration Applications

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's G...

Pinchuk, P. et al The National Renewable Energy Lab (NREL)

Oct 15, 2024
4 Resources
0 Stars
In progress

County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model

This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly ...

Cole, W. et al National Renewable Energy Laboratory (NREL)

Aug 01, 2023
5 Resources
1 Stars
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ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and hi...

Speake, A. et al National Renewable Energy Lab

Mar 03, 2023
6 Resources
0 Stars
Curated

Imperial Valley Dark Fiber Project Continuous DAS Data

The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...

Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory

Nov 10, 2020
4 Resources
0 Stars
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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
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Airfoil Computational Fluid Dynamics 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes ...

Ramos, D. et al National Renewable Energy Laboratory (NREL)

Feb 10, 2023
3 Resources
0 Stars
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Airfoil Computational Fluid Dynamics 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes w...

Ramos, D. et al National Renewable Energy Laboratory (NREL)

Feb 10, 2023
3 Resources
0 Stars
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Hourly Dynamic Line Ratings for Existing Transmission Across the Contiguous United States (Preliminary)

This dataset provides estimated hourly dynamic line ratings for ~84,000 transmission lines across the contiguous United States from 2007-2013. The calculation methods are described in the presentation linked below, and the associated open-source Python code repository is linked in...

Obika, K. et al National Renewable Energy Laboratory

Sep 25, 2024
16 Resources
0 Stars
Curated

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
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SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS

The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the data...

Palmintier, B. et al National Renewable Energy Laboratory (NREL)

Dec 18, 2020
5 Resources
0 Stars
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EGS Collab Experiment 1: Microseismic Monitoring

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...

Schoenball, M. et al Lawrence Berkeley National Laboratory

Jul 29, 2019
45 Resources
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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
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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
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