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Carolinas Engine Data Explorer - Prototype

Story Maps

About the Carolinas Engine for Grid Modernization – Prototype

The Motivation

The Carolinas Engine for Grid Modernization Explorer Prototype was developed to provide a mapping platform for a shared, evidence-driven view of grid reliability, workforce readiness, and regional economic conditions. By integrating innovation indicators at both county and sub-county levels, the prototype offers a tool for targeting efforts and monitoring impact over time.

The structure of the Explorer was designed to integrate indicators across six categories: Energy, Education & Workforce, Economic Wellbeing, Research & Development, Economic Environment, and Business Conditions. With the framework in place, we are actively incorporating indicators and have completed the Energy, Education & Workforce, and Economic Wellbeing sections. Please check back as the work progresses.

The interface is open-source HTML, CSS, and JavaScript built with Bootstrap and Leaflet. The basemap is sourced from OpenStreetMap.

Key Mapping Features
  • Engine Region of Service (ROS). While the Engine’s region of service is the focus, all counties in North and South Carolina are included to provide context and acknowledge that boundaries are fuzzy and fluid. Partners and impacts may extend into neighboring counties, and the region of service may evolve as the ecosystem builds.
  • Spatial and Temporal Features. The interface includes interactive maps, variable descriptions, and time-series graphs. Core functions include zooming, transparency controls for viewing reference maps, and downloading publicly available data.
Instructions:

Data can be mapped by clicking on the category across the top of the display and then clicking on one of the subcategories. The data will then display. Then, the user can zoom in/out. To return to the ROS, click on the small home button under the slider tool. To view data for a particular area, click on a specific county/area; the display category in which the area falls will be highlighted on the right in blue, and the graph over time will change according to that county/area as compared to the average for all counties across the two states. The transparency can be changed by sliding the fill bar.

Style control and home button example
Disclaimer

The Carolinas Engine for Grid Modernization Explorer uses publicly available data from various government and third-party sources. We attempt to provide accurate and timely information, but cannot guarantee the completeness, precision, or reliability of the data presented. This tool is for informational, guidance, and planning purposes. We are not responsible for decisions made based on this tool. Inclusion of any location, entity, or dataset does not imply endorsement or affiliation. For details on data, please consult the references provided. By using this interface, you acknowledge and accept these limitations.

Creators

Moses Asori (Lead, Developer & Designer)

Doctoral Candidate in Geography, UNC Charlotte

Tyler Cox (Developer)

Business Systems Analyst II, UNC Charlotte

Dr. Deborah S.K. Thomas (Designer)

Associate Vice Chancellor for Research & Professor of Geography, UNC Charlotte

Data Sources and Processing

Links are placeholders — refine as you verify.
Variable Source (Citation / Link) Data Processing Procedure
System Average Interruption Duration Index (SAIDI) Keeler et al. (2024) — National Science Foundation NHERI The data at the county level was available as a modelled output by Keeler et al. (2024). However, it was between 2013 and 2020. To obtain for 2024 and 2000, regression-based forecast and backcast were conducted using the year as the random effect.
System Average Interruption Frequency Index (SAIFI) Keeler et al. (2024) — National Science Foundation NHERI The data at the county level was available as a modelled output by Keeler et al. (2024). However, it was between 2013 and 2020. To obtain for 2024 and 2000, regression-based forecast and backcast were conducted using the year as the random effect.
Customer Average Interruption Duration Index (CAIDI) Derived from SAIDI/SAIFI Compute SAIDI ÷ SAIFI per county.
Estimated Household Natural Gas Use Department of Energy (2019) — Department of Energy The data was a modelled output by the Department of Energy for 2013–2020. To obtain values for 2024 and 2000, regression-based forecast and backcast were conducted using year as a random effect.
Estimated Household Electricity Use Department of Energy (2019) — Department of Energy The data was a modelled output by the Department of Energy for 2013–2020. To obtain values for 2024 and 2000, regression-based forecast and backcast were conducted using year as a random effect.
Estimated Household Use of Liquid Fuels Department of Energy (2024) — Department of Energy The data was a modelled output by the Department of Energy for 2013–2020. To obtain values for 2024 and 2000, regression-based forecast and backcast were conducted using year as a random effect.
U.S. Electric Power Transmission Lines ArcGIS National Maps (ND) — ArcGIS National Maps No transformation except for clipping to NC and SC state boundaries.
U.S. Electric Grid Stations Synapse Energy Economics Inc (2025) — Synapse Energy Economics, Inc. No transformation except for clipping to NC and SC state boundaries.