Alternatives to Contour Visualizations for Power Systems Data

Isaiah Lyons-Galante, Morteza Karimzadeh, Sam Molnar, Graham Johnson, Kenny Gruchalla

Room: 103

2023-10-21T22:00:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
A synthetic electrical grid covers a neighborhood in Oakland, CA. This network includes over 24,000 junctions, or buses, each with a given voltage at a single snapshot in time. Here, we surrounded each bus with a Voronoi polygon. The electrical state of the network is represented by coloring each polygon by the bus voltage. A blue-white-red diverging color scale shows deviations from the expected voltage. Giving each bus its own polygon increases the fidelity of the visualization to the real data distribution by avoiding averaging. We explore this and other alternatives to contour visualizations for power systems data.

Electrical grids are geographical and topological structures whose voltage states are challenging to represent accurately and efficiently for visual analysis. The current common practice is to use colored contour maps, yet these can misrepresent the data. We examine the suitability of four alternative visualization methods for depicting voltage data in a geographically dense distribution system—Voronoi polygons, H3 tessellations, S2 tessellations, and a network-weighted contour map. We find that Voronoi tessellations and network-weighted contour maps more accurately represent the statistical distribution of the data than regular contour maps.