As artificial intelligence (AI) technology rapidly advances, Texas is emerging as a global battleground for data center dominance. Yet behind this technological revolution looms a crisis: the state’s power grid is struggling to keep pace. The Electric Reliability Council of Texas (ERCOT) predicts that by 2030, Texas will need to add electricity equivalent to the output of 30 nuclear reactors to meet soaring demand from data centers, Bitcoin mining, and hydrogen production.
Texas’ grid is under unprecedented strain. ERCOT forecasts that peak electricity demand will skyrocket to 149 gigawatts (GW) by 2030—a 75% jump from the current record of 85.5 GW. This sharp revision reflects the explosive growth of AI-driven data centers, now the primary driver of energy consumption.
We’re entering uncharted territory where massive industrial loads could directly threaten grid reliability, warned Agee Springer, ERCOT’s senior manager of grid interconnections, at a recent summit in Austin. Individual data center projects are now requesting up to 1 GW of power—enough to supply 250,000 Texas homes—while total new grid connection requests have surged to 99 GW, more than double the 40.8 GW reported last March.
Texas’ grid vulnerabilities were laid bare during the catastrophic 2021 winter storm blackouts. Now, the influx of power-hungry AI data centers is pushing the system to its limits. ERCOT internal reports warn that failure to balance supply and demand could trigger grid collapse under extreme conditions.
Electricity supply must outpace demand growth, or the consequences will be dire, said Beth Garza, senior fellow at the R Street Institute. But challenges abound: supply chain delays for critical equipment like turbines and transformers, sluggish permitting for new transmission lines, and the multibillion-dollar question of who will foot the bill for infrastructure upgrades.
Texas’ “Four Coincident Peaks” (4CP) program—designed decades ago to incentivize industrial users like refineries to cut power during summer peaks—is under fire. By reducing usage during critical periods, these operators avoid contributing to grid upgrade costs, effectively shifting the financial burden to households and small businesses.
This cost-sharing model is no longer fair as reliability risks shift, argued Texas Senator Charles Schwertner during the summit. A proposed state Senate bill seeks to overhaul the 4CP system, demanding that “all ratepayers share costs equitably.”
With time running out, nuclear energy—praised for its reliability and low-carbon profile—is gaining traction as a solution. Resmi Surendran, Shell Energy’s VP of regulatory policy, noted that data centers adopting “demand response” (adjusting usage based on price signals) could alleviate grid stress. However, profitability challenges loom: data centers struggle once prices exceed $2,000 per megawatt−hour, yet ERCOT’ sprice cap stands at $2,000 per megawatt−hour, yet ERCOT’s price cap stands at $5,000.
Can Texas build the equivalent of 30 nuclear reactors’ capacity by 2030? Uncertainty reigns. But one thing is clear: the outcome of this high-stakes clash between AI ambition and energy infrastructure will reshape the future of U.S. tech.
