GridSync

GridSync finds where neighboring utilities' planned power-line projects overlap in place and time, then turns each match into a coordination plan with a savings estimate.

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Inspiration

  • Utilities often plan projects separately.
  • Nearby projects can happen at the same time without coordination.
  • GridSync helps utilities find these opportunities and work together.
  • Built for the Sperry Gridlock Challenge.

What it does

  • Shows utility projects on an interactive map.
  • Finds projects within 25 miles of each other.
  • Checks if construction dates overlap.
  • Ranks opportunities by distance, timeline, and compatibility.
  • Lets users search and filter projects.
  • Shows project details, budgets, schedules, and sources.
  • Compares projects side by side.
  • Estimates possible cost and land savings.
  • Uses AI to explain opportunities, risks, and next steps.
  • Creates email drafts and meeting invites.
  • Flags delayed projects.
  • Supports Excel data uploads and web research.

How we built it

  • React + Vite for the frontend.
  • Django for the backend.
  • MongoDB Atlas for the database.
  • Google Maps for the project map.
  • Gemini for AI analysis.
  • Render for deployment.
  • Used real utility planning documents for project data.
  • Calculated distance between nearby projects.
  • Compared construction dates for schedule overlap.

Challenges

  • Some projects had missing coordinates.
  • Some budgets were not available.
  • Some projects shared the same substation.
  • Utility documents had different formats.
  • Keeping AI answers based only on real data.
  • Connecting the frontend, backend, database, maps, and AI.

Accomplishments

  • Found all 6 reference overlaps.
  • Built automatic project matching.
  • Connected project information to source documents.
  • Built an adjustable savings estimator.
  • Built AI-generated project analysis.
  • Added utility outreach and meeting tools.
  • Deployed GridSync at usegridsync.us.

What we learned

  • How utility transmission planning works.
  • Good data is very important.
  • AI should explain data, not invent it.
  • Utilities can save resources by coordinating nearby projects.

What's next

  • Analyze 250+ utility projects.
  • Add natural-language map search.
  • Add a what-if schedule slider.
  • Add more utilities and regions.
  • Improve automatic project research.

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