ERCOT issues Batch Zero conditional classifications after an August 31 delay

On August 31 at 7:16 p.m., ERCOT Market Notice M-A080326-03 delayed Batch Zero conditional classifications that had been targeted for that day, citing unfinished data validation and due diligence and promising release later in the week. Batch Zero is the first cohort under ERCOT’s system-wide interconnection study for qualified large loads of at least 75 megawatts. On September 3 at 3:55 p.m., Market Notice M-A080326-04 said ERCOT had notified each Interconnecting Distribution Service Provider and Transmission Service Provider of the provisional classification of the Large Loads those utilities submitted. The notice says each load may be conditionally included subject to conditions such as the Interconnecting Large Load Entity passing verification, curing dynamic-model data deficiencies, or the PUCT granting ERCOT a good-cause exception (regulator permission to qualify a load that missed an eligibility requirement at submission). Failure to meet an applicable condition can knock a load out of Batch Zero. Loads submitted as base load but conditionally classed as studied load can use the Planning Guide Section 9.3.1(2)(a) dispute path; utilities must notify the load entity within two business days; Alternative Dispute Resolution under Protocol Section 20.4 remains available for exclusions. Some loads submitted as already energized that do not qualify on that path may get fourteen business days to refile under a different eligibility subparagraph while ERCOT seeks a separate PUCT exception—otherwise they wait for a future study batch. The notices do not publish a public project list, megawatt totals, or named campus owners, and they do not authorize energization.

Why it matters

Conditional classification was the week’s central Texas interconnection gate: it starts dispute and cure clocks and keeps verification and community-impact work pointed at the December 10 report track, but it is not final Batch Zero membership and does not clear energization of large computational loads.

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