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Grid Care tells Utah regulators AI, 'qualified flexibility' can unlock transmission capacity for data centers
Summary
Grid Care told the Utah Public Service Commission that AI-driven analysis and a framework for 'reliability‑backed' customer flexibility could open existing transmission capacity — estimating a U.S. planning‑peak utilization upper bound near 32% and proposing hour‑based interconnection offers for large loads.
Grid Care co‑founder and CTO Ran Rajikop told the Utah Public Service Commission that a Stanford‑linked study and Grid Care’s own modeling put a U.S. planning‑peak transmission‑utilization upper bound near 32%, and that raising that utilization through qualified, reliability‑backed flexibility could free hundreds of gigawatts of capacity.
"32% is our upper bound estimate of the utilization of the grid overall in the United States," Rajikop said, describing a methodology that measures per‑element utilization at the planning peak and averages across N‑1 contingency dispatch scenarios.
The company presented a three‑part approach: identify when and where capacity is constrained (hour and contingency), qualify offered resources (batteries, front‑of‑meter generation, diesel or other options) against those specific needs, and require activation, real‑time monitoring and independent verification so the flexibility is "reliability‑backed," Rajikop said.
Jessica Hogal, Grid Care’s head of government and regulatory affairs, said the approach is intended to work with — not replace — utilities’ traditional planning tools. "The output of the flexibility calculations ... can then be run through the utilities' legacy planning tools so they have comfort with it," she said.
Grid Care described a computational strategy that evaluates a very large space of spatial, temporal and contingency scenarios (the presenters cited an illustrative 21‑quadrillion scenario search) and then distills results into conventional planning files that utilities can validate. Rajikop emphasized the calculation is a "snapshot" at the one‑in‑20‑year planning peak and acknowledged a full 8,760‑hour, year‑round analysis would typically show lower average utilization.
Commissioners and staff questioned the methodology and how it differs from utility metrics. Rajikop said differences often come from scope (systemwide average versus selectively reported elements) and metric definitions, and offered to compare methodologies directly: "We made this study completely public and all the methods are published and open," he said.
Grid Care argued the practical outcome would be an interconnection process that negotiates deliverable hours per year — a curve rather than an absolute yes/no — allowing large loads faster access to some capacity in exchange for bounded, auditable flexibility commitments.
The presenters acknowledged hurdles: planners’ and operators’ conservative contingency practices, data confidentiality and cybersecurity requirements, and incentive alignment inside utilities. They recommended clear qualification rules, SOC‑compliant data processes and regulatory incentives or performance mechanisms to align utility decisionmaking with the proposed fast‑track processes.
The company offered to run scenario comparisons with Utah utilities and to deliver outputs formatted for legacy planning tools so staff can validate the results in their existing models. The presentation concluded with an offer to help draft framework language and implementation steps for a conditional, reliability‑backed interconnection track.
What happens next: commissioners and staff will consider the information and follow up questions on methodology, confidentiality safeguards and the regulatory incentives necessary to adopt a qualified‑flexibility fast track.
