Catalyst N° 077 of 125 12 Sep 2025
When to colocate data centers with generation
with Brian Janous, co-founder and chief commercial officer, Cloverleaf Infrastructure
In this note
The question
When does it actually make sense to build generation on site at a data center, and when has the idea simply become fashionable?
The answer
Almost never for the reasons usually given: Janous argues the economics are bad, the speed advantage is weaker than it looks because gas pipelines are congested too, and the premise underneath both is wrong, since utilities are trying to survive a handful of peak hours rather than match a 24/7 load with a 24/7 machine. The version that holds up is using on-site resources to shrink how large you look to the grid, and even there generation competes with storage, demand response and grid upgrades. The weak point he concedes is that this alternative requires orchestration across thousands of utilities.
03The argument
Start with the clarification that reframes everything. Nearly every cloud data center already has generation on site: diesel backup gensets, sized for rare transmission-level outages and limited by air permits that cap runtime and eat into the allowance needed just to test them. What is new is generation meant to be prime power, running close to around the clock alongside a grid connection. The case for it has two parts. First, speed: if the utility says five to seven years for a connection at the scale you want, building your own might be faster. Second, that a 24/7 load needs a 24/7 generation source to match it, an argument Janous hears from the current administration as a case for more baseload plants and calls flatly false.
He attacks the second part first, because it decides what problem you are solving. A utility does not study whether it can supply you across all 8,760 hours of the year. It asks whether adding you pushes the system past what it can serve on the hottest summer afternoon and the coldest winter morning. That makes this a capacity problem rather than an energy problem, and capacity problems have far more solutions than building a machine that runs constantly. Janous describes the grid as moving power through space and time, so its pieces substitute for each other: a transmission line substitutes for baseload generation, since moving power across congestion reduces what has to be generated locally, and long-duration storage substitutes in turn for transmission. Add grid-enhancing technologies, advanced conductors, storage of varying durations and virtual power plants, and you can replicate a 24/7 output with a dozen things instead of one, faster because much of it already exists and cheaper because you build less.
The economics are unattractive, though not disqualifying. Work the arithmetic on a 100-megawatt data center: a power usage effectiveness of 1.2 puts you at 120 megawatts of generation, redundancy adds 20 or 30 more, so you build 150 and run it at perhaps 90 on average, because data centers chronically underuse nameplate. At roughly $2,700 per kilowatt with an overbuild approaching 2x, the cost per kilowatt-hour is extraordinarily high: in Texas something like $150 to $200 per megawatt-hour around the clock, while the data center next door buys grid power near $20 and the old reason to own a baseload machine there, occasional scarcity prices of $5,000 to $9,000, has been decimated by solar and storage. But Kann turns Janous’s own bit-watt spread back on him: electricity is small against what a data center earns, so a developer might pay the premium for speed anyway. Janous concedes it, probably in a lot of cases. Overpaying is not a deal killer, just no economic benefit and worse margins than a competitor who got grid access.
Which leaves the version both accept: not going off-grid, but shrinking your interconnection footprint, siting a 500-megawatt data center where the utility can deliver 300 and holding your grid draw under that ceiling. Janous agrees, then reframes it as orchestration, because behind-the-meter generation is only one way to fill the gap. A long-duration battery on the utility’s side of the meter might do the same job, and the fastest option builds nothing: aggregate enough sheddable load inside the deliverable zone that the utility credits it as capacity. Nobody has done that at real scale, and vertically integrated utilities object that they want rate base rather than a program, to which Janous answers that a virtual power plant is a bridge letting them connect the load sooner and build against it later. The limit he volunteers is that this is where his argument may fall apart: orchestrating across roughly 3,000 US utilities and several regional markets with different accreditation rules is hard, and the tool that would price a stack of capacity options for any point on the grid, trusted by utility and developer alike, does not exist. On-site nuclear, meanwhile, fails every test at once. It is not faster, not cheaper early, you will already hold your full interconnection by the time it arrives, and no one plugs a $20 billion facility into a novel reactor without a decade of operating data.
04What you need to know first
- Behind the meter
- Generation on the customer’s side of the utility meter, serving the facility directly instead of selling into the grid.
- Capacity versus energy
- Utilities plan against system peaks, not annual consumption, so anything that cuts your draw in those few hours can substitute for generation that runs all year.
- Capacity accreditation
- How much of a resource’s nameplate rating a grid operator counts as firm. It decides whether batteries or shed-able load can stand in for a generator in an interconnection decision.
- The bit-watt spread
- Janous’s term for the gap between what electricity costs a data center and what the compute earns. It is wide enough that power price is rarely the deciding factor.
05Details worth keeping
- AI training sites are moving away from backup generators, partly because a training run can tolerate a rare outage and partly because diesel at gigawatt scale is difficult to permit in most markets. xAI’s Colossus site did build them anyway, though Janous notes it is smaller than recently announced sites, citing 1.3 gigawatts in Port Washington, Wisconsin and around 1.4 in Abilene.
- Going off-grid assumes gas is available where electricity is not. Janous says gas congestion is real and you cannot put a pipe in the ground anywhere and get unlimited supply.
- Data centers have always been microgrids, designed for two power sources, but reaching the redundancy an engineer expects from an islanded system requires a significant overbuild.
- On-site wind and solar combinations work where land is abundant, such as West Texas, but stay a small share of the market because most demand wants to sit near major metros.
- Both speakers are bullish on new nuclear in the US generally. The objection is specifically to putting it behind a data center’s meter.
06Claims worth citing
All figures as stated on 2025-09-12, attributed to the speaker rather than independently verified. Equipment prices and interconnection timelines move fast.
- Roughly $2,700 per kilowatt for on-site generation, described as a rough number. Janous
- Worked example, not a measured case: 100-megawatt data center, power usage effectiveness of 1.2, plus 20 to 30 megawatts of redundancy, giving about 150 megawatts built against a 90-megawatt average draw. Janous
- One data center operator reported average utilization of 40% to 50% of nameplate over a year. unnamed operator, cited by Kann
- Off-grid power in Texas at roughly $150 to $200 per megawatt-hour around the clock versus a real-time grid price near $20, with Janous noting he excludes transmission and distribution charges from the grid side. Janous
- ERCOT scarcity prices used to reach $5,000 to $9,000 per megawatt-hour and have largely stopped appearing; Kann agrees volatility there is down. Janous, Kann
- Utilities quoting five to seven years for large connections, given as the premise of the speed argument rather than a surveyed figure. Janous
- Roughly 3,000 utilities in the United States. Janous
- No credible argument for behind-the-meter nuclear for the next couple of decades, with about ten years of operating data needed before anyone connects a $20 billion to $50 billion facility to a new reactor design. Janous
- An 11-gigawatt campus near Amarillo is mentioned, but the transcript garbles the developer’s name, rendering it as the company named earlier for 100-hour batteries. Check it before repeating. Kann, Janous
07Where it’s contested
- Janous names his own weak point. Asked whether the multi-resource approach can be done programmatically rather than as bespoke deals, he says this is where his argument maybe falls apart. It has to work across thousands of utilities and several regional markets with different accreditation rules, and the software that would make it routine does not exist yet.
- How much grid headroom exists is a judgment call. Kann frames the disagreement explicitly: the prevailing view is that necessity forces colocation even when it is suboptimal, while Janous thinks more interconnection capacity is reachable on a reasonable timeframe. Janous confirms that is his view. Neither offers data; it is a difference in expectation.
- He is a commercial participant in the answer he prefers. Janous says Cloverleaf’s business is working with utilities case by case to connect load faster, the same approach he argues should win.
- Using demand response as interconnection capacity is untested. Kann knows of nobody who has implemented it and notes accreditation at that level is nuanced and geographically constrained. Janous agrees no one has done it at real scale, says Cloverleaf is close on a couple of projects and expects it soon. That is a forecast from an interested party.
- Firm gas supply is raised and then parked. Janous questions whether a firm gas connection is obtainable, then explicitly sets the issue aside.
- The cost argument does not settle the decision. Janous accepts developers may build uneconomic on-site generation anyway, because revenue from operating sooner outweighs the power premium.