2028년 40GW+ 돌파, 데이터센터 직접 발전으로 눈을 돌리는 AI 기업들

US Grid Constraints: Towards 40GW+ of Behind-The-Meter Datacenter by 2028? Why the Grid Can't Keep Up, and Why that Drives Behind-The-Meter 50%+ of DCs/Year By 2028 Jeremie Eliahou Ontiveros , Sebastian Orejas , Ellie Holbrook , and Dylan Patel Jun 25, 2026 ∙ Paid 149 9 14 Share Today, the US grid is serving most datacenter load in the US, but we’re reaching a tipping point. As the insatiable demand for power of AI Labs and hyperscalers keeps accelerating, the grid simply can’t add capacity fast enough. That leaves Behind-The-Meter as the only way for the largest players to secure the power they need . Nearly a year ago, our Onsite Gas deep dive was the first to predict the fast rise of new entrants in the BTM gas equipment market. Since then, companies like Bloom Energy, Bergen Engines, W ärtsilä and many others have been remarkably successful. Overcoming GEV and Siemens turbine capacity constraints proved far easier than many had feared . Today, we go deeper and model US Grid capacity to understand the shortfall that must be filled by Behind-The-Meter solutions for datacenters. Let’s start with key numbers: first, we continue to see a record datacenter buildout in the US, going from +21GW in 2026 to +84GW by 2030. We explained in detail last week why Datacenter Delays headlines are often overblown . Our research suggests that BTM will power well over half of new US datacenters in 2028+ , and the Total Addressable Market (TAM) for DC BTM equipment to cross 50GW/ year by 2029. New Grid Capacity isn’t growing fast enough, and also needs to serve non-datacenter load growth. The chart above shows the three core building blocks of our forecast: Expected Datacenter US Gross Power Demand, available US Grid Capacity, and New Grid Supply. We use the best of SemiAnalysis industry-leading insights to build this forecast. T he first block, datacenter demand, comes from a b ottom-up forecast powered by a building-by-building model , supported by chip-by-chip AI demand forecast of the Accelerator Model , and validated by our Tokenomics Model which tracks the economics of the buildout and answers the “bubble” question . T he second building block of our Energy Model , grid headroom, analyzes supply & demand dynamics in each major part of the US grid. Our model follows the methodologies of all ISOs & RTOs and models UCAP/ICAP reserves, supply & demand growth, reliability risks, etc. The third block forecasts new grid supply, through a b ottom-up forecast produced by our new Energy Model . We track 40,000 generation assets in the US and forecast quarter by quarter Commercial Operation Date (COD) for all fuel types. We then estimate the “true” capacity value of power plants via our proprietary ELCC model, adapting to the specifics of each ISO and major non-ISO region . Our forecast points to barely 15GW of net-new ELCC capacity being added annually, with a rising trend towards 20GW+ by the end of the decade. This is effectively all the firm capacity being added to the system that a grid operator can recognize to serve firm datacenter load - as well as other firm load like industrial plants, semiconductor fabs, etc. Netting that accredited supply against peak demand and required reserve margins is what yields headroom itself, the spare accredited capacity a market has left to host new load after covering its own peak demand and required reserve margin. On this basis, available headroom is already approaching zero and turns negative by 2027, based on our analysis of required reserve margins across the country. As such, we expect power generation to be a major bottleneck to grid-connected datacenter load growth (transmission is another one and will be the topic of a follow-up deep dive). All datacenter operators have already seen this firsthand : a utility tells you it can meet a 2027 load-ramp schedule, e.g. , 500MW, and later comes back saying they can only deliver that load only in 2029 because the long-lead equipment grid interconnection requires, from main power transformers (MPTs) to high-voltage breakers and, in some cases , network upgrades, simply is not available any sooner. Worse, the burden increasingly falls on the buyer : securing grid-connected power now often requires developers to post substantial letters of credit, security deposits, or sign take-or-pay commitments to fund the generation built to serve their load. Switch Datacenter, for instance, closed a multi-billion-dollar performance letter-of-credit facility in 2026 to back exactly these obligations. And in many cases, despite billion-dollar commitments, the utilities don’t even face any penalties for not delivering on time. Subscribe These generation and transmission constraints, combined with inadequate market incentives, makes Behind-The-Meter often the most attractive solution for GW-scale newbuilds. And we’re already observing that many top-tier developers are planning 5GW+ behind-the-meter facilities in Texas, where permitting onsite gas is easier. Our Datacenter Model covers this in extreme detail , separating the few « real » 5GW+ campuses from those that show no sign of credible development under the hood. This is, of course, a material tailwind for BTM solutions and providers. However, key beneficiaries aren’t the usual suspects. A few months ago, we were the first to flag the risk of temporary peak gas turbine orders. Read our Core Research report “ Grid Power Bad, BTM Good” – Peak Gas Turbine Orders, IPPs Challenged, But Grid Equipment Demand Accelerating ” for more details. Our new Energy Model is the best tool to forecast and understand relative market positioning by company: we track manufacturing capacity, equipment lead times, installation lead times, major deal announcements, and much more. We’ve also covered recent secondary-market developments in depth, with notably surging turbine availability . Let’s dig in. Our argument runs in three steps, and this report walks through them in order: grid supply is structurally constrained, that constraint pushes the marginal buyer behind the meter, and that shift reshuffles the winners and losers across equipment OEMs and IPPs as the market grows across fully islanded and hybrid BTM setups. First, we establish the supply constraint: drawing on our new Energy Model , we explain how we forecast power-plant additions, how we estimate the true capacity value of each fuel via ELCC, and how we measure the grid headroom that results . Next, we turn to the buyer’s decision: the relative attractiveness of BTM versus grid for the largest buyers of power and compute, broken down by use case. Finally, we examine the practical bridge between them: the hybrid co-location structures emerging in ERCOT — codified by the Batch Zero process — that blend on-site generation with continued grid access, and where we think the early winners are taking shape. We explain more on this later. Note that this article focuses on grid constraints and behind-the-meter as a solution, but there are alternatives, like Load Flexibility. These will be the focus of future deep dives, and out of scope for this one. We briefly explain later in this article why we think BTM will be the prominent solution over alternatives like Load Flexibility. SemiAnalysis is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe Forecasting Power Plants: No Gas Until 2028 Our analysis of 40k generators reveals one of the core challenges for the US grid: the lack of firm, dispatchable capacity added to the market over the next two years. Our nameplate capacity forecast shows that the US industry will add less than 10GW of gas per year in 2026 and 2027, with additions only picking up in 2028 and beyond. To achieve this forecast, we replicate our Datacenter Model methodology: it starts with an extensive analysis of construction timelines, with hundreds of thousands of empirical datapoints analyzed, backed by real-time sate