Robin Gaster
The explosive growth of artificial intelligence (AI) also implies rapid growth of electricity demand, for the first time in several decades. Previously, growing electrification had been roughly matched by growing efficiency, leaving demand flat. That is now changing, quite rapidly. OpenAI and the other AI companies are seeking out sources that can provide multiple gigawatts of energy, so they certainly believe demand is growing. Beyond data centers, more electric vehicles (EVs) and the electrification of homes and industries add to demand as well.
Supply is another matter. It takes time to add generating capacity to the grid, and more time to develop the transmission lines to move electricity to where it’s needed. That in part is why huge new AI campuses are being designed: AI companies can then control their own energy generation (“behind the meter”) and don’t have to worry as much about transmission.
But all that new capacity is some years away. Manufacturers have a five-year backlog for gas turbines. Solar is quicker to build but harder to permit, and locations are usually not that close to demand so transmission is needed. New-build nuclear is at least a decade away. And while we strongly support data centers bringing their own energy supplies “behind the meter,” even that will take considerable time.
Data centers therefore seek electricity from the existing grid. And the grid has a fundamental dilemma. In the early 20th century, the U.S. grid emerged from a period of competition into geographically separated monopolies. It made no sense to build separate competing wires everywhere, and electricity companies quickly became vertically integrated, managing electricity generation, transmission, and distribution. Those monopolies were closely regulated and not just for price (“rates”); the utilities needed permission to add capacity because that meant adding cost, for example.
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