Quenching Data Center Thirst for Power Now Is Solvable Problem

With energy demand soaring — largely due to the growth of data centers supporting a burgeoning AI industry — concerns have arisen about where the nation will find the energy capacity to meet its power needs.

A new report by the Information Technology and Innovation Foundation (ITIF) argues that capacity can be found in the near- and medium-term, giving power providers the time they need to add infrastructure to the existing grid and meet longer-term electricity demand.

“However, such a solution will not arrive on its own,” wrote the author of the report, Robin Gaster, research director for ITIF’s Center for Clean Energy in Washington, D.C. “Without significant action across multiple fronts and at substantial scale, the existing grid will come under increasing pressure — and we can expect a massive struggle for access.”

“Regulators will be caught between the sudden growth in demand and political pressure to service existing commercial and residential customers first, while keeping a lid on prices,” he explained.

One of the significant drivers of the growing electricity demand appears to be data centers, the report noted, prompting calls to slow their growth or even prevent them from connecting to the grid altogether.

“Slowing data center growth or prohibiting grid connection is a short-sighted approach that embraces a scarcity mentality,” argued Wannie Park, CEO and founder of Pado AI, an energy management and AI orchestration company, in Malibu, Calif.

“The explosive growth of AI and digital infrastructure is a massive engine for economic, scientific, and industrial progress,” he told TechNewsWorld. “The focus should not be on stifling this essential innovation, but on making data centers active, supportive participants in the energy ecosystem.”

“Data centers are the engine of the AI economy, but they can’t be passive loads anymore,” he said. “Data centers can and should be active partners that contribute to grid stability and resilience, not just consume power. Prohibiting growth would simply limit the innovation needed to solve the power crunch in the first place.”

Smart Integration Needed

The reality is the U.S. has dramatically underinvested in long-term grid upgrades and planning, maintained Scotty Embley, an associate with Hi-Tequity, a data center development and investment firm, in Melbourne Beach, Fla. Slowing data center builds equates to slowing vital applications such as banking, federal, health care, and transportation, he told TechNewsWorld.

However, he acknowledged that early coordination with utilities is necessary to ensure new facility locations are strategically planned and responsibly powered, where adequate grid support is available.

Instead of restricting data center development, the focus should be on smarter integration with the grid, added Allan Schurr, chief commercial officer at Enchanted Rock, a provider of natural gas-powered microgrids, in Houston.

Planning for the full lifecycle of a data center’s power needs — from construction through long-term operations — is essential, he continued. This approach includes having solutions in place that can keep facilities operational during periods of limited grid availability, major weather events, or unexpected demand pressures, he said.

Schurr explained that on-site generation, including natural gas microgrids, can provide bridge power during interconnection delays, flexible capacity to support grid-constrained regions, and dependable backup power when the grid is stressed or offline. With this type of coordinated approach, data centers can continue to grow while strengthening, not straining, our power infrastructure, he contended.

Data centers are the source of the information for anything we do on the internet, added Arie Brish, a business professor at St. Edward’s University in Austin, Texas. They must be up 24/7. These facilities are not like a laundry operation that can be limited to off-hours.

He also noted that the importance of continuity in data center operations requires that they have backups of local generators. These local generators can indeed be used to feed the facilities during peak hours, thus balancing grid demand, he told TechNewsWorld.

Getting More From Existing Infrastructure

Rick Bentley, CEO of HydroHash, a crypto-mining company focused on clean energy and high-efficiency operations, in Albuquerque, N.M., recommended that data center operators avoid the grid entirely. That saves the data center massive costs in both regulations and fees, he told TechNewsWorld.

Once they are on the grid, their power can be curtailed during times of high demand to make sure the heat stays on in people’s homes during a cold snap, hospitals stay operational, and A/C works during a heat wave, he explained.

The ITIF report also called for the United States to squeeze more power from the existing grid without negatively impacting customers, while also building new capacity.

New technology can increase supply from existing transmission lines and generators, the report explained, which can bridge the transition to an expanded physical grid.

On the demand side, it added, there is spare capacity, but not at peak times. It suggested that large users, such as data centers, be encouraged to shift their demand to off-peak periods, without damaging their customers. Grids do some of that already, it noted, but much more is needed.

Up to 40% of data centers’ needs are not highly time sensitive, so they can be partners in managing peak demand by proactively shifting some of their use to different times and even different geographies, it reasoned.

AI’s Strain on the Grid

Ironically, AI, a significant driver of data center power usage, can also help squeeze more electricity from the existing grid.

We need to map energy delivery with the same supply chain visibility we apply to national defense — using AI to map where power is wasted, where infrastructure is stalled due to fragile supply chains and where capacity is trapped behind inefficient legacy systems, Brandon Daniels, CEO of Exiger, a developer of AI-powered risk, compliance and supply chain management solutions, in McLean, Va., told TechNewsWorld.

Pado’s Park agreed that one of the best ways to maximize existing grid capacity is to leverage software and AI/ML to balance power supply and demand better. Implementing orchestrated demand through advanced software for demand-side flexibility can intelligently coordinate large, flexible loads — like data centers — with grid signals, he noted.

The primary challenge is the speed of deployment and regulatory lag, he said. Data center growth is moving at an unprecedented pace, and traditional utility planning and regulatory approval processes struggle to keep up, for good reasons.

Additionally, he continued, data centers operate under stringent reliability requirements, aka “five nines,” which create technical and contractual hurdles to integrating load flexibility at scale.

Embley, of Hi-Tequity, asserted that the U.S. can squeeze more capacity from the existing grid by putting underutilized or stranded power to work — whether through repurposing industrial sites that already have heavy electrical infrastructure or tapping idle substations and interconnects built for past manufacturing loads.

These approaches deliver relief far faster than building new transmission, he explained. The challenge is that grid stress is already the top obstacle utilities cite, and major upgrades move on decade-long timelines. Interconnection queues continue to grow, and even when capacity exists on paper, critical equipment like transformers and switchgear carry 12- to 24-month lead times, which often slow projects more than construction itself.

He added that computing density has changed dramatically as the use of artificial intelligence continues to soar. Today’s AI clusters draw 30 to 60 kilowatts per cabinet, two to three times the load of legacy CPU racks, overwhelming the electrical and thermal systems built for a different era, he explained.

At the same time, grid expansion, interconnection, and long-lead electrical equipment operate on decade-long timelines, while AI demand is rising on year-long timelines.

That mismatch, he said, not a lack of ambition or innovation, is what’s driving the current power crunch.