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A group of energy researchers have a three-part prescription for Washington, D.C.’s exploding energy costs.

Washington, D.C. has earned an unwelcome distinction: the largest one-year electricity price increase of any state (or equivalent geographic distinction) in the U.S. Prices there are up 87% over the past five years and 26% in the past year alone, according to new data from MIT and Heatmap News’ Electricity Price Hub. The average D.C. household is now paying $55 more for power each month than it did five years ago.
In the face of this crisis, local officials have done little but blame regional markets, emphasizing the parts of recent rate increases they don’t fully control — generation charges — rather than any proactive measures they could take to offer relief to D.C. households. Meanwhile Exelon, the parent company for Pepco, D.C.’s local utility, has used the crisis to lobby state policymakers across the region for something worse — a return to utility-owned generation, which could leave consumers holding the bag for projects that run over budget or that are built for demand that never materializes.
As residents of Washington, D.C. and energy researchers who helped put together the Electricity Price Hub, we are well aware that the District cannot remake the regional electricity market on its own. But it has meaningful tools to protect ratepayers now.
To be sure, the problems D.C. faces are not entirely of its own making. Rising demand and constrained supply across the Mid-Atlantic have created a wholesale market pressure cooker.
Capacity market prices in the Pepco region, which are set through a regional auction scheme designed to ensure the grid can reliably deliver power when demand peaks, increased more than fivefold in 2025. Those costs are passing through to retail bills. As capacity has come under increasing strain, generation charges in Pepco’s standard supply service have gone up 119% — 33% in the past year alone, with yet another rate increase set to kick in on June 1.
That regional dynamic is real. But it does not absolve local officials.
Roughly 30% of Pepco’s average residential bill is made up of charges that fall squarely under D.C. jurisdiction. Distribution charges, the largest of those local components, have risen 57% over five years, and account for 20% of the total rate increase. The D.C. Public Service Commission regulates utilities in the District and must approve Pepco’s rates before they take effect. The commission, in turn, answers to the D.C. Council, the District’s legislature, which confirms its commissioners and oversees its work. These bodies should be examining every dollar of Pepco’s proposed increases. Instead, a D.C. court recently struck down the commission’s most recent rate-hike approval, finding that it had failed to sufficiently scrutinize Pepco’s request.
When a regulator is doing such a poor job that judges have to step in, that is a five-alarm signal. Yet there is a workable action plan for the Council and the PSC to rein in costs and ease the burden on D.C. households.
First, scrutinize distribution charges aggressively — that is squarely within their jurisdiction. As Pennsylvania Governor Josh Shapiro argued in his public letter to utility leaders last month, the PSC should require Pepco to justify every additional dollar of revenue requested in plain language. That means using transparent, replicable data and analysis to show why it’s needed, the alternatives considered, and how the proposed spending will concretely benefit consumers. To support this, the D.C. Council should ensure that the PSC, the Office of the People’s Council, and relevant state agencies are adequately resourced and positioned to engage with and probe Pepco’s arguments in rate proceedings.
Second, force transparency into how Pepco procures power. The public has remarkably little visibility into what makes up generation charges for the utility. For example, how much of the total cost is attributable to capacity prices, energy procurement, administrative costs, and compliance with the District’s Renewable Energy Portfolio standard? And what changes could D.C. consider to the competitive procurement process or RPS eligibility requirements to mitigate costs? Officials can’t manage what they can’t measure.
Third, attack demand by making it easier for customers to generate their own supply. High and unpredictable interconnection fees, process delays, and other administrative hurdles add unnecessary costs and contribute to the above-average cost of solar in D.C.. The D.C. Council and PSC can incentivize distribution-level solar battery deployment by cutting permitting and interconnection costs and improve cost transparency and streamline interconnection reviews to speed up the process of installing solar and storage.
None of these moves alone will reverse five years of rate increases. But together they would put real downward pressure on bills and signal that the city is serious.
What officials should reject — across the region — is Exelon’s push for utility-owned generation. In practice, it could create a generation subsidiary tomorrow. The reason it wants its rate-regulated distribution utility to do so instead is that this would let it earn a guaranteed return on costs it currently just passes through, while shifting the risk of cost overruns, schedule slips, and overbuilt capacity from shareholders to ratepayers. It would also hand the utility an information advantage over independent power producers, suppressing the competition the market relies on to keep prices honest. More profit, less risk, less competition. A great deal — for the utility.
The D.C. Council recently passed emergency legislation pausing utility disconnections for residents with unpaid balances under $1,000. That is a humane stopgap as we head into summer, but it is not a strategy. Neither is anything that has been proposed during the current mayoral race, in which leading candidates have attacked each other’s records instead of offering a plan to lower bills.
D.C. residents do not need more blame-shifting. The choice in front of the council and the PSC is concrete: Scrutinize what is in their jurisdiction, force the transparency they have the authority to require, accelerate the cheapest sources of new supply, and refuse to subsidize a Pepco business model that turns ratepayers into the underwriters of utility risk. That is the test of whether they meet this moment seriously.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation. What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.