Alternatives to Contour Visualizations for Power Systems Data

Isaiah Lyons-Galante; Morteza Karimzadeh; Samantha Molnar; Graham Johnson; Kenny Gruchalla

doi:10.1109/EnergyVis60781.2023.00009

Alternatives to Contour Visualizations for Power Systems Data

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

Computational Science

University of Colorado Boulder

Research output: Contribution to conference › Paper

2 Scopus Citations

Abstract

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.

Original language	American English
Pages	11-15
Number of pages	5
DOIs	https://doi.org/10.1109/EnergyVis60781.2023.00009
State	Published - 2023
Event	2023 Workshop on Energy Data Visualization (EnergyVis) - Melbourne, Australia Duration: 22 Oct 2023 → 23 Oct 2023

Conference

Conference	2023 Workshop on Energy Data Visualization (EnergyVis)
City	Melbourne, Australia
Period	22/10/23 → 23/10/23

NREL Publication Number

NREL/CP-2C00-87207

Keywords

power systems
tessellation
visualization

Access to Document

10.1109/EnergyVis60781.2023.00009

Cite this

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title = "Alternatives to Contour Visualizations for Power Systems Data",

abstract = "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.",

keywords = "power systems, tessellation, visualization",

author = "Isaiah Lyons-Galante and Morteza Karimzadeh and Samantha Molnar and Graham Johnson and Kenny Gruchalla",

year = "2023",

doi = "10.1109/EnergyVis60781.2023.00009",

language = "American English",

pages = "11--15",

note = "2023 Workshop on Energy Data Visualization (EnergyVis) ; Conference date: 22-10-2023 Through 23-10-2023",

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TY - CONF

T1 - Alternatives to Contour Visualizations for Power Systems Data

AU - Lyons-Galante, Isaiah

AU - Karimzadeh, Morteza

AU - Molnar, Samantha

AU - Johnson, Graham

AU - Gruchalla, Kenny

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - power systems

KW - tessellation

KW - visualization

U2 - 10.1109/EnergyVis60781.2023.00009

DO - 10.1109/EnergyVis60781.2023.00009

M3 - Paper

SP - 11

EP - 15

T2 - 2023 Workshop on Energy Data Visualization (EnergyVis)

Y2 - 22 October 2023 through 23 October 2023

ER -

Alternatives to Contour Visualizations for Power Systems Data

Abstract

Conference

NREL Publication Number

Keywords

Access to Document

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Cite this