[K0balt]

I manage a solar micro grid that powers 9 Holmes, a small farm, and several other structures and utilities.

We use intelligent power management over the fiber network to tell certain loads when to turn on or off or to change their operating parameters based on power conditions.

I’ve been daydreaming about building a ml based forecaster that just gives the next few hours weather outlook based on pressure, temperature, humidity, and a wide Nigel image of the sky.

I know it is doable because I can do it myself, and probably without any intuition about the pressure. It would automatically calibrate the model wights by feedback from the actual events vs the forecast. This would be really useful for me at least, in managing battery usage and otherwise managing the various systems that store energy like air compressors and large mass refrigeration.

[rl_for_energy]

Not the exact same but some similar work on wind: https://www.deepmind.com/blog/machine-learning-can-boost-the...

[cosmic_shame]

This sounds interesting, whereabouts?