Press resource · Following the research
Working press resource. Studies are posted as they come out, whatever they find. Each entry links to the primary source. Last verified July 11, 2026. On deadline: 850.973.7687
I am trying to follow the research wherever it leads. My argument is not that data center demand pushes prices up or down. It is a principle that holds either way: companies should not be allowed to externalize costs while internalizing profits. Cost means total cost: economic, environmental, social, and quality of life. Data centers and utilities are today's example. The principle is the point.
"Both sides in this debate reach for the number that flatters their case. I am less interested in whether the average went up or down than in a question the average cannot answer: when a data center triggers a billion dollars in new capacity, who pays for it. That question survives every study."
This page is where I track credible studies as they come out, whatever they find. When the research is strong, I say so. When it complicates my thinking, I say that too. The goal is an honest read, not a scoreboard.
Entry one · July 2026
Researchers Asa Watten, John Bistline, and Geoffrey Blanford estimate that data centers caused average retail electricity rates in the United States to fall modestly between 2015 and 2024. Their reasoning is economies of scale. A power system carries large fixed costs. When durable demand grows, those costs spread across more kilowatt-hours, so the average unit price falls. Their preferred estimate is that a doubling of data center capacity lowers residential prices by about 3.5 percent. In the states where capacity grew fastest, they find residential rates fell around 6 percent.
Two of the three authors are affiliated with the Electric Power Research Institute. EPRI is an independent, nonprofit research organization. It is not owned by utilities, and I am not suggesting the work is compromised. It does collaborate closely with utilities, and readers deserve to know where research comes from. I include this as disclosure, not to discredit. The study is careful, and I take it seriously.
The mechanism is real. Spreading fixed costs over more usage can lower average prices. That is standard economics, not spin. The analysis is methodical, and its central finding for the 2015 to 2024 period belongs on the table. The study also went looking for something I care about and did not find it. The authors tested whether data centers were shifting costs onto residential customers during this period, and their data show no systematic cost-shifting between customer classes. I take that finding at face value. It is a fair result for the years they studied.
First, this measures a period that is mostly behind us, before the demand that started this whole debate. The study covers 2015 to 2024. ChatGPT did not launch until late 2022, so most of the window predates the AI surge entirely. More important is the kind of growth the study captures. New demand lowers average prices only when the system has slack. EPRI's authors are explicit about the reverse: if anticipated load from data centers materially exceeds realized consumption, "utilities risk overbuilding capacity whose fixed costs would be spread across fewer kWhs, reversing the mechanism we identify." The study describes a grid with room. That is not the grid Florida is about to have. The build-out now underway, running to 2030, is exactly that reverse case: concentrated, fast, and requiring new generation and transmission. So the study does not contradict my concern. It describes the conditions under which its own finding flips, and those are the conditions we are entering.
Second, a falling average is not the same as a fair allocation. The study measures average rates across a state. My argument is about who pays for the specific new capacity a single large customer triggers. Even if the average falls, the question of whether the party that caused a new line or plant paid for it, or passed it to everyone else, is a different question. An average cannot answer it. Only looking at who bears the specific cost can.
Third, the forward-looking research points the other way. A March 2026 Dallas Fed analysis projects that data centers will raise the electricity component of inflation through retail prices, by a small amount now and more by 2030, with slower renewables growth making it worse. The same analysis notes that current connection fees tend to be modest, leaving existing customers on the hook for grid expansion. I do not cite this to claim prices will rise. I cite it to show the evidence genuinely points in more than one direction, which is the honest state of the question right now.
EPRI's own researchers recommend the policy I am arguing for. On supply constraints, they write that price increases "can be avoided entirely by delaying interconnection or allocating the inflated incremental cost of grid expansion to rates paid by data centers." They name the states already doing it: Kansas, Michigan, and Delaware, which have pursued minimum bills or long-term contracts from new large loads. This is worth stating plainly because the study is being cited as a rebuttal to cost allocation, and its discussion section recommends cost allocation.
Whether average rates rose or fell, the question I care about does not change. Did the party that triggered the new capacity pay for it, or did others. That is a question about allocation, and it survives whatever the average does.
Every study on this page links to its primary source, verified before publishing. The framing is deliberately economic. The question throughout is cost causation and cost allocation: who triggers the buildout, and who pays for it. Reporters and editors are welcome to reach out for a source interview.
Contact: Dr. Mark R. McNees, Florida State University, mmcnees@fsu.edu, 850.973.7687