Cost-Causation
State & Regional Interventions
Protect Ratepayers from Subsidizing the Costs of Data Centers
Utilities must ensure that the costs of energy infrastructure to serve data centers are not unfairly passed on to ordinary customers. Special consideration should be paid to ensure that all costs associated with the development of data centers—including construction and energy generation—are paid for by data centers, not taxpayers. Require Data Centers to Pay Separately […]
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Utilities must ensure that the costs of energy infrastructure to serve data centers are not unfairly passed on to ordinary customers. Special consideration should be paid to ensure that all costs associated with the development of data centers—including construction and energy generation—are paid for by data centers, not taxpayers.
Require Data Centers to Pay Separately for 100 Percent of the Necessary Costs to Service Them
Data centers must be required to pay separately for 100 percent of the costs necessary to service them, including transmission, energy generation, capacity, and financing costs.1
Transmission lines are the network of high-voltage power lines that carry energy from power generation stations (power plants) to local distribution systems (the local wires that enter our homes and schools). The cost-causation principle, which guides ratemaking, says that customer prices should align with the costs necessary to provide service to that customer—meaning that customers can and should pay proportionally for the transmission lines that service them. However, recently, ratepayers have disproportionately paid for regional transmission costs tied to data center growth. States must pass legislation that directly allocates costs to data center customers that use or are able to use more than 20 megawatts (MW). For recommendations on defining data centers and setting rate classes, see Develop Separate Rate Classes for Large-Load Customers below.
example
A bill proposed in Georgia, SB34, prohibits electric utility companies from including costs necessary to service commercial data centers in their rates, unless costs are charged exclusively to data centers or prorated based on demand. The bill specifically calls out costs associated with increased fuel requirements, generation costs, and transmission costs.
Example
SB 6 in Texas requires large-load customers (75 MW or more) to fund transmission fees and upfront costs in the data center development process. However, the bill explicitly greenlights new behind-the-meter gas-powered power generation for data centers, which we recommend states prohibit.
Institute an Equitable Tariff Schedule
A tariff schedule, the official pricing structure set by utility companies, includes rates per unit of energy and other charges (such as service fees). Large-load customers must be subject to a tariff schedule that is equal or proportional to the costs of serving them, mitigating the risk that other classes of retail consumers are paying unwarranted costs. This may include instituting a new tariff schedule or amending an existing tariff schedule.
Strong example
Previously in Oregon, large industrial users like data centers were paying about 8 cents per kilowatt hour (kWh), while residential customers paid 20 cents per kWh. The newly proposed tariff schedule institutes a rate that will ensure data centers pay their fair share.
Investigate or Revise Cost Allocation Methodology and Formulas
To assign costs to various ratepayer classes, utilities use a wide variety of methods, all of which lead to varying results.2 Some utilities use methods that assign more costs to customers with peaking energy demand, like residential customers, and fewer costs to data center customers. Regulators must investigate whether existing cost-allocation methodologies are fair, and enact provisions to revise methodologies that unfairly burden ordinary ratepayers for the costs associated with data centers.
Strong example
In 2024, Virginia introduced a bill that directs the State Corporation Commission to initiate proceedings to determine if the current allocation of costs among different customer classifications are fair, and to determine whether customers that are not data centers are subsidizing the costs of data center customers.
Directly Allocate Additional Fees to Data Centers Where Applicable
Utilities are authorized to directly allocate costs in certain situations. These include fees for capacity studies, tracking cost allocation, revenue tracking, or purchased-power adjustments.
Strong example
Ohio requires new data centers to pay study fees that range from $10,000 to $100,000.
Require Data Centers to Fund Independent Cost Studies
Require data centers to fund third-party, independent studies investigating whether additional costs are passed on to consumers throughout the data center generation process, including:
- Whether higher costs get passed on to all customers, as data centers are raising capacity costs
- Whether data center-created supply constraints are going to make energy projects more expensive
- Whether customers are paying for financing or early construction costs for new infrastructure before the large-load customers come online
Strong example
California’s SB 57 directs the California Public Utilities Commission (CPUC) to assess costs that could result in cost-shifting to other ratepayers, including costs related to utility procurement operations and installation of new transmission and distribution assets.
Federal Interventions
Mobilize Authority Under the Federal Energy Regulatory Commission (FERC) to Oversee Data Centers
Reject Colocation Policies That Enable AI Data Centers to Soak Up Available Energy In December 2025, FERC announced that PJM Interconnections’s tariff governing the colocation of generation with large loads like AI data centers was unjust due to unclear and inconsistent rates and terms. FERC directed PJM to create transparent, enforceable tariff rules for such […]
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Reject Colocation Policies That Enable AI Data Centers to Soak Up Available Energy
In December 2025, FERC announced that PJM Interconnections’s tariff governing the colocation of generation with large loads like AI data centers was unjust due to unclear and inconsistent rates and terms.1 FERC directed PJM to create transparent, enforceable tariff rules for such arrangements and new transmission service options in order to protect consumers “by keeping electricity costs manageable.”2 Moving forward, FERC action can clarify that colocation policies not disproportionately ease barriers for such AI data center projects.
Enshrine the 2024 FERC Order
Enshrine the November 2024 FERC order,3 which determined that shifting existing generation away from the bulk power market to serve a data center is unjust and unreasonable.4
Mandate Load Flexibility Programs and Interconnection Requirements
Direct FERC to mandate load flexibility programs and forced curtailment procedures for data centers5 and update large-load interconnection requirements to prevent cascading outages.6
Compel the Collection and Publication of Energy-Use Data
Direct FERC and/or the U.S. Energy Information Administration (EIA) to compel the collection and publication of energy-use data by data centers, and compel FERC to require disclosure of when power sellers are affiliated with data centers.7
Note: Although disclosure of water consumption is also important for data center transparency, FERC does not have jurisdiction over water usage. This recommendation should also be accompanied with provisions that assign appropriate authority over water transparency metrics. For more details, see “Require Comprehensive Transparency Mechanisms and Monthly Reporting.”
Revise Cost-Allocation Methodologies
Direct FERC to mandate that regional transmission organizations (RTOs) such as PJM revise their transmission cost-allocation methodologies so that other customers are not subsidizing the construction of transmission lines that are needed solely to serve data centers.
Reject Nondisclosure Agreements in Utility and RTO Proceedings
The federal government should prohibit the use of nondisclosure agreements (NDAs) in utility and RTO proceedings. If that is not possible, condition eligibility for any preferential rate tariffs or access to interconnection queues on not employing nondisclosure agreements related to development deals.
Correct Misalignment Between Utility Incentive Structures and Public Interest
Direct FERC to undertake a systematic review of transmission incentive adders and to take other steps necessary to correct misalignment of utility incentive structures with the public interest to ensure that utilities are not overbuilding the transmission system in response to underscrutinized load growth projections.
Protect Against Overbuild
Direct FERC to maintain and regularly update a national database of proposed data centers, working closely with utility commissions and regional transmission operators to accurately forecast load increases, predict accurate infrastructure needs, and protect against overbuilds.8
- Federal Energy Regulatory Commission, “Fact Sheet: FERC Directs Nation’s Largest Grid Operator to Create New Rules to Embrace Innovation and Protect Consumers,” December 18, 2025, https://www.ferc.gov/news-events/news/fact-sheet-ferc-directs-nations-largest-grid-operator-create-new-rules-embrace. ↩︎
- Ibid. ↩︎
- PJM Interconnection, L.L.C., Order Rejecting Amendments to Interconnection Service Agreement, 189 FERC ¶ 61,078, November 1, 2024, https://www.ferc.gov/sites/default/files/2024-11/20241101-3061_ER24-2172-000.pdf. ↩︎
- Thanks to Public Citizen for this recommendation. See Deanna Noel and Meghan Pazik, “Reining in Big Tech: Policy Solutions to Address the Data Center Buildout,” Public Citizen, December 3, 2025, https://www.citizen.org/article/reining-in-big-tech-policy-solutions-to-address-the-data-center-buildout. ↩︎
- Ibid. ↩︎
- Matthew McHale and Hannah Wiseman, Nine Ways to Address the Energy Impacts of AI Data Centers, Vanderbilt Policy Accelerator, January 2026, https://cdn.vanderbilt.edu/vu-URL/wp-content/uploads/sites/412/2026/01/12211201/Nine-Ways-to-Address-the-Energy-Impacts-of-AI-Data-Centers.pdf. ↩︎
- Thanks to Public Citizen for this recommendation. ↩︎
- McHale and Wiseman, Nine Ways to Address the Energy Impacts of AI Data Centers. ↩︎
