Integrated solar abundance → AI cluster sizing with LFP battery chemistry, thermal runaway safety, and full cost modeling.
This optimizer unifies the two sides of the clean-compute equation — solar generation and data-center demand — into one model, so you can right-size a facility and its power plant together rather than in isolation.
It's for anyone planning solar-powered compute who needs to see generation and load balance across the day.
The model overlays a solar generation profile on the facility's demand and uses storage to bridge the gap, reporting how much of the load is served cleanly and how much needs backup. Optimising means finding the capacity-and-storage mix that maximises coverage per dollar.
Treating supply and demand as one system avoids the classic mistake of sizing panels and load separately, which either wastes generation or leaves the facility grid-dependent.
Balancing a compute load against a solar field plus storage shows the sweet spot where added panels stop helping and storage starts to — the practical recipe for a mostly-clean data center.
The planner sizes demand; this optimizer balances generation and demand together for best coverage.
It focuses on capacity and coverage; treat cost with adjustable assumptions.
Often close, with enough storage; the model shows the diminishing returns.
No — a transparent first-order optimizer.
Yes — 25 languages, in-browser.