Grid-Bridge

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Inspiration

Utilities publish future power-grid projects in separate plans. That makes it hard to see when nearby work from different utilities might create a chance to coordinate. The Gridlock Challenge asked us to make those connections easier to find.

We were also inspired by the WGDSS approach described in the project strategy: turn multiple data sources into clear, explainable guidance for people making operational decisions. We brought that idea to long-term utility planning.

What it does

Grid-Bridge compares planned projects from Dominion Energy South Carolina and Georgia Power. It shows project locations on an interactive map, measures the closest distance between project geometries, and ranks potential coordination opportunities.

For each opportunity, Grid-Bridge explains why the pair was flagged and shows the available source and confidence information. When timeline information is available, it can help planners assess whether coordination may be timely. Missing construction dates remain unknown rather than being guessed.

The platform can also help planners explore potential impact ranges using explicit assumptions. These are planning scenarios, not guaranteed savings or utility cost estimates.

How we built it

We organized project information into a consistent format, then used a deterministic spatial engine to compare project geometries and calculate their closest points. A backend evaluates project pairs and supplies the map and ranked opportunity view. Google Maps provides the visual interface.

The system separates measured spatial results from sponsor baseline comparisons and scenario assumptions. That way, planners can see what the data supports and where further verification is needed.

Challenges we ran into

Public plans do not always provide precise locations or construction windows. Some projects have only one location point; others have endpoints but no verified route between them. We represent those records honestly and label approximate geometries instead of presenting them as surveyed infrastructure.

We also learned that comparing project centers can miss important relationships. A long line can pass close to another project even when its center is far away, so Grid-Bridge measures between the project geometries themselves.

Accomplishments that we're proud of

Grid-Bridge turns separate public plans into an explainable cross-utility view. It evaluates all 25 DESC–Georgia Power project pairs, surfaces six current candidate opportunities, and shows why each pair falls into its proximity tier.

We’re proud that the map, ranking, and explanations are grounded in deterministic results, while data limitations remain visible. The system helps identify where coordination may be worth investigating without claiming that approximate lines are real shared routes.

What we learned

Spatial proximity is a useful starting point, not proof that projects can share crews, land, equipment, or schedules. Good planning tools need to distinguish what is known from what still needs validation.

We also learned that transparent methods matter: planners should be able to trace an opportunity back to its project data, understand why it was flagged, and see where assumptions begin.

What's next for Grid-Bridge

Next, we want to add verified project alignments and construction windows as public sources become available, then connect the spatial applicability results to the Impact Engine’s planning scenarios. We also want to expand the public project set and gather planner feedback so the opportunities are more useful in real coordination discussions.

Built With

• api
• codebase
• cross-utility
• github
• google-directions
• google-places
• integrated-earth-data-applications
• python
• utility
• webgl