FERC Orders PJM to Clarify Rules for Data Centers Co-Located With Power Plants
The Federal Energy Regulatory Commission has directed PJM Interconnection to establish clearer and more transparent rules for serving large electricity loads, including AI-driven data centers, that are co-located with generating facilities.
The order applies to PJM, the regional grid operator serving more than 67 million people across 13 states and Washington, D.C. FERC said the changes are needed to safeguard grid reliability and ensure consumers are protected from unjust or unreasonable rates.
“Today’s order is a monumental step toward fortifying America’s national and economic security in the AI revolution, while ensuring we preserve just and reasonable rates for all Americans,” said FERC Chairman Laura Swett. “I look forward to tackling more of these critical national issues with my colleagues in the New Year.”
In its order, the commission found PJM’s tariff unjust and unreasonable because it lacks clear and consistent rates, terms and conditions for interconnection customers serving co-located load, as well as for transmission customers taking service on those loads.
FERC said the tariff also fails to adequately address transmission service arrangements in which eligible customers manage energy withdrawals for co-located load. As a result, the commission directed PJM to revise its tariff to require eligible transmission customers serving co-located load to select from a defined set of transmission service options.
“Clarifying new rules will help release the bottleneck of large load investments across the PJM footprint,” said FERC Chairman Laura Swett.
FERC also ordered PJM to submit a report by Jan. 19, 2026, detailing progress on proposals intended to accelerate the addition of new generating capacity. Those proposals include an expedited interconnection process for projects that are ready to build, potential changes to PJM’s reliability backstop mechanism for capacity shortfalls, and improved load forecasting and demand flexibility measures to better identify future reliability needs.