Visualization Encoding Experiments for Power Systems Analysis
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Through a human factors study, we evaluated the use of contour and glyph visualizations for two modern power systems models: an urban distribution model and a large-scale transmission model. This dataset provides model data and scripts for recreating the power flow data and visualizations used in the study, in addition to the study results and statistical analysis.
Citation Formats
TY - DATA
AB - Through a human factors study, we evaluated the use of contour and glyph visualizations for two modern power systems models: an urban distribution model and a large-scale transmission model. This dataset provides model data and scripts for recreating the power flow data and visualizations used in the study, in addition to the study results and statistical analysis.
AU - Gruchalla
A2 - Molnar
A3 - Johnson
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - visualization
KW - distribution systems
KW - transmission systems
LA - English
DA - 2022/10/27
PY - 2022
PB - National Renewable Energy Laboratory
T1 - Visualization Encoding Experiments for Power Systems Analysis
UR - https://data.openei.org/submissions/8251
ER -
Gruchalla, et al. Visualization Encoding Experiments for Power Systems Analysis. National Renewable Energy Laboratory, 27 October, 2022, NREL. https://data.nrel.gov/submissions/200.
Gruchalla, Molnar, & Johnson. (2022). Visualization Encoding Experiments for Power Systems Analysis. [Data set]. NREL. National Renewable Energy Laboratory. https://data.nrel.gov/submissions/200
Gruchalla, Molnar, and Johnson. Visualization Encoding Experiments for Power Systems Analysis. National Renewable Energy Laboratory, October, 27, 2022. Distributed by NREL. https://data.nrel.gov/submissions/200
@misc{OEDI_Dataset_8251,
title = {Visualization Encoding Experiments for Power Systems Analysis},
author = {Gruchalla and Molnar and Johnson},
abstractNote = {Through a human factors study, we evaluated the use of contour and glyph visualizations for two modern power systems models: an urban distribution model and a large-scale transmission model. This dataset provides model data and scripts for recreating the power flow data and visualizations used in the study, in addition to the study results and statistical analysis.},
url = {https://data.nrel.gov/submissions/200},
year = {2022},
howpublished = {NREL, National Renewable Energy Laboratory, https://data.nrel.gov/submissions/200},
note = {Accessed: 2025-05-31}
}
Details
Data from Oct 27, 2022
Last updated Jan 21, 2025
Submitted Oct 27, 2022
Organization
National Renewable Energy Laboratory
Contact
Kenny Gruchalla
