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WIND Toolkit Long-Term Ensemble Dataset
WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indica...
Wang, J. et al National Renewable Energy Laboratory (NREL)
Jan 24, 2024
3 Resources
1 Stars
In curation
3 Resources
1 Stars
In curation
Battery inverter experimental data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We used controllable AC supply...
Prabakar, . et al Power Systems Engineering
Jan 06, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
PV inverter experimental data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, . et al Power Systems Engineering
Jan 06, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Split phase inverter data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 8.35 kW off-the-shelf grid following split phase PV inverter in the experiments. We used controllable ...
Prabakar, . et al Power Systems Engineering
Mar 23, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
PV inverter experimental dataset version 2 with 100 percent power
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, . et al Power Systems Engineering
Nov 10, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes model...
Buster, G. et al The National Renewable Energy Lab (NREL)
Oct 16, 2024
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
Publicly accessible
9 Resources
1 Stars
Publicly accessible
Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America
This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a genera...
Zeng, Z. et al Argonne National Laboratory
Oct 03, 2023
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...
BushNREL
Aug 01, 2020
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
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
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Caerbannog Point Clouds
The Caerbannog Point Clouds provide point-sampled 3D models occluded in clouds of points. We synthesized the 3D point clouds from polygonal models, point-sampling the models and surrounding them in a point cloud such that the shape of the model is occluded in any 2D projection. We...
Raghupathi, . et al NREL
Dec 01, 2020
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible