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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
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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
4 Resources
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...

Ahmmed, B. Stanford University

Apr 04, 2022
3 Resources
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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
1 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
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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
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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...

Tripp, C. et al National Renewable Energy Laboratory

Dec 30, 2022
9 Resources
1 Stars
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INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...

Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)

May 04, 2021
8 Resources
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Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...

Ayyanar, R. et al Arizona State University

Feb 01, 2025
12 Resources
0 Stars
In curation

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
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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
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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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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 National Renewable Energy Laboratory (NREL)

Apr 19, 2023
7 Resources
2 Stars
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Utah FORGE 2-2446: Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity using Phase-Field Simulations

This report presents a series of numerical experiments investigating the relationships among near-well fracture complexity, in situ stress conditions, and wellbore deviation. Using a phase-field modeling approach, the study explores how factors such as stress regimes, wellbore ori...

Cusini, M. and Fei, F. Lawrence Livermore National Laboratory

Jan 30, 2025
2 Resources
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EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...

Chai, C. et al Oak Ridge National Laboratory

Apr 20, 2020
7 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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AlphaBuilding Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with...

Li, H. et al Lawrence Berkeley National Laboratory

Dec 21, 2020
5 Resources
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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
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Highly-resolved, Long-term Energy Demand Projections for the Contiguous United States: Data Compiled Using the Demand-side Grid (dsgrid) Toolkit for the Integrated Energy Futures Project

Modeled and compiled datasets describing electricity use by sector, and end use that are geographically specific, hourly, and projected out to 2050 for a single scenario. The current datasets reflect a scenario with a high degree of end-use electrification moderated by high assume...

Hale, E. et al National Renewable Energy Laboratory (NREL)

Feb 04, 2025
2 Resources
0 Stars
In progress

The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017

The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a uni...

McMillan, C. et al National Renewable Energy Laboratory (NREL)

Jul 01, 2024
4 Resources
0 Stars
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2023 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2023 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

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

Jun 09, 2023
13 Resources
0 Stars
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2024 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2024 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

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

Jun 24, 2024
14 Resources
1 Stars
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Distributed Generation Market Demand (dGen) model

The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sector...

Stanley, T. et al National Renewable Energy Laboratory (NREL)

Oct 16, 2020
4 Resources
1 Stars
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2022 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2022 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products ...

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

Jun 01, 2022
14 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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