In the News
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‍Latitude Media recently featured an article by Bianca Giacobone exploring how speculative data center load requests—many of which never materialize—are overwhelming utilities and distorting grid planning forecasts. As large tech firms “queue shop” for available power, utilities are left struggling to distinguish viable projects from “phantom” ones, leading to delayed timelines, inflated load projections, and misallocated resources.

GridUnity CEO Brian Fitzsimons shares that nearly 30% of load connection applications submitted to one of their major utility clients in 2024 were later canceled. He points to outdated tools and lack of standardization as key issues, noting that “many transmission owners have been handling these processes using spreadsheets and project binders.” Fitzsimons advocates for transparency and a more standardized process—paired with commercial and financial readiness screenings—to bring greater accountability and clarity to the system.

This piece highlights:

• The rise of “phantom” data center load requests flooding utility queues
  
  
• How speculative applications distort load growth forecasts and delay real projects
  
  
• The need for transparency, screening, and standardization to restore efficiency and trust in the load interconnection process
  
  

It’s a valuable read for anyone interested in grid modernization, utility planning, and managing large load growth in the AI era.
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Read the full article here: https://www.latitudemedia.com/news/phantom-data-centers-are-flooding-the-load-queue

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GridUnity Take

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At GridUnity, we see this story as a clear signal that utilities need modern tools to manage an evolving load landscape. As speculative requests cloud the queue, our solutions—like GridInterConnect and GridSync—help utilities enforce transparency, assess commercial readiness, and bring standardization to their load connection processes.

We believe the future of reliable grid planning requires smarter screening, open data, and a digital-first approach to manage load growth at scale.

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