"Womp Womp! Your browser does not support canvas :'("

Visualization Encoding Experiments for Power Systems Analysis

Publicly accessible License 

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, Kenny A2 - Molnar, Samantha A3 - Johnson, Graham DB - Open Energy Data Initiative (OEDI) DP - Open EI | National Laboratory of the Rockies 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 -
Export Citation to RIS
Gruchalla, Kenny, et al. Visualization Encoding Experiments for Power Systems Analysis. National Renewable Energy Laboratory, 27 October, 2022, NREL. https://data.nlr.gov/submissions/200.
Gruchalla, K., Molnar, S., & Johnson, G. (2022). Visualization Encoding Experiments for Power Systems Analysis. [Data set]. NREL. National Renewable Energy Laboratory. https://data.nlr.gov/submissions/200
Gruchalla, Kenny, Samantha Molnar, and Graham Johnson. Visualization Encoding Experiments for Power Systems Analysis. National Renewable Energy Laboratory, October, 27, 2022. Distributed by NREL. https://data.nlr.gov/submissions/200
@misc{OEDI_Dataset_8251, title = {Visualization Encoding Experiments for Power Systems Analysis}, author = {Gruchalla, Kenny and Molnar, Samantha and Johnson, Graham}, 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.nlr.gov/submissions/200}, year = {2022}, howpublished = {NREL, National Renewable Energy Laboratory, https://data.nlr.gov/submissions/200}, note = {Accessed: 2026-06-09} }

Details

Data from Oct 27, 2022

Last updated Mar 12, 2026

Submitted Oct 27, 2022

Organization

National Renewable Energy Laboratory

Contact

Kenny Gruchalla

Authors

Kenny Gruchalla

National Renewable Energy Laboratory

Samantha Molnar

National Renewable Energy Laboratory

Graham Johnson

National Renewable Energy Laboratory

Share

Submission Downloads