Comment by bob1029
Comment by bob1029 a day ago
From a purely engineering perspective I think it becomes difficult to argue with the gas turbine once you get into the gigawatt class of data center. The amount of land required for this much solar is not to be understated. In many practical scenarios the solar array would need to be located a distance away from the actual data center. This implies transmission infrastructure which is often the hardest part of any electrical engineering project. You can put a gigawatt of N+1 generation on a 50 acre site with gas. It's dispatchable 24/7/365 and you can store energy for pennies on the dollar at incredible scale.
Having both forms of generation available at the same time is the best solution. Once you put a data center on the grid you can mix the fuel however you want upstream. This should be the ultimate goal and I believe it is for all current AI projects. I am not aware of any data center builds that intend to operate on parking lot generators indefinitely.
For inference you don’t need gpus to be clustered together as much (generally training has lots of synchronisation steps so you can be bottlenecked on that instead of ‘real’ work) as they can handle separate tasks in parallel. But maybe other economies of scale still make you want to put them together (and therefore on average further from the power).
I guess there was a bit of thought about transmission with the reference to high voltages. Another interesting thing: batteries allow you to reduce the needed capacity for transmission lines – if you have batteries near generation and then transmit power at a lower maximum, same average rate than if you only have batteries near use, you can more efficiently use the available transmission.
I guess the main reason for gas to be a problem is if you can’t get new generation (eg lack of turbines).