u/Born_Proof_9010 — reddlx

I looked at this white paper and I’m not sure that I’m sold on their supercapacitor’s ability to smooth out the volatility for large load swings that these AI data centers are supposedly experiencing. I am also not an electrical engineer so I could be dead wrong but here is what I am curious about:

On page 8, it shows a graph of how the supercapacitor is able to accommodate the volatility. The example used is a 300 kilowatt load with swings between 40% and 100%, cycling between the min and max about once per minute. In this example, it appears that the supercapacitors are able to do the job for this load profile. However, from what I’ve heard, these large AI data center loads are orders of magnitude larger than that and can swing between 40-50% around 10 times per minute and even multiple times per second. For example, a site with a peak load of 160 megawatts swinging 60-80 megawatts 10 times per minute. 160mw is over 500 times larger than 300kw. Can the supercapacitors handle that? Let’s assume that all of the supercapacitors together could handle an 80mw swing at a 160mw site once per minute. Could it handle 10 times per minute? If a supercapacitor has a lifespan of 1,000,000 cycles, at 3,000 cycles per day (~2 cycles per minute) the lifespan is less than 1 year.

I assume that the 300kw load in their example is meant to reflect extreme conditions on a single GPU rack, and obviously there are multiple supercapacitors at work here inside the data center. I don’t know how all of this works in terms of coordination between the racks but I still am interested in seeing how Bloom Energy’s solution will solve for these wild fluctuations.

https://www.bloomenergy.com/wp-content/uploads/load-following-solid-oxide-fuel-cell.pdf

I have a few questions that I am hoping someone can address. I listened to a Suncast Media podcast recently with the CEO of Terraflow Energy who basically described serious problems that AI data centers are running into regarding load profiles. I think it is well worth the listen if anyone is interested in this topic. https://www.youtube.com/watch?v=ga3m191bg34

Terraflow’s solution, as I understand it, is vanadium flow batteries. I think they are basically suggesting running a grid connected data center load through the batteries constantly, not just using them for back up. Unlike lithium, they say that vanadium flow batteries do not experience the wear and tear (or thermal runaway) of constant on/off cycles that you would see with lithium batteries performing the same function. He also outlines that turbine or engine generators are not a viable solution long term given that it appears that these data centers are burning through physical components of the generators (crankshafts, switches, etc.) at an unsustainable level. This is due to the extremely volatile load profile and the need for the generators to constantly kick on/off to maintain a steady load for the grid. Terraflow’s solution makes sense for grid connected AI data centers, but I assume it would also work the same for completely islanded data centers that are running off of some other base load power.

Bloom Energy’s stock price has skyrocketed recently. Presumably, this is due to the idea that a completely islanded AI data center (what their solution can help provide) is preferable to a grid connected one. I am wondering though, if islanded sites will be running into the same issues as grid connected sites. The grid operators will obviously not accept any sort of interruption due to the load volatility, hence the proposed Terraflow solution. However, in an islanded data center situation, I would think that the downside shifts squarely to the AI model companies, who will suffer high latency or even straight up outages (lack of compute) if the generators fail due to overuse. My questions are therefore:

1. Assuming that these AI companies don’t care how many generators they burn through to keep the tokens flowing, how long can that last?

2. For an islanded data center, does Bloom Energy’s solution provide the base load power or is their solution meant to be the back up or load smoothing enabler (similar to Terraflow)?

3. If Bloom Energy’s solution is being used at grid connected AI data centers as back up, can their solution kick on quickly enough to maintain smooth load back onto the grid?

4. If Bloom Energy is the baseload power at an islanded site, aren’t the AI companies still at risk of compute outages or latency issues due to the same generator issues those sites would be subject to?

5. Do software solutions, such as Emerald AI, that spread out the AI workloads across data centers eventually solve this problem for good?

Thank you!