A space solar power and data station does two jobs at once: it collects sunlight far above weather and night, and it decides how to use that power — running AI compute on board, beaming energy down to Earth, or both. This designer sizes such a station end to end and exposes the trade-offs that actually decide whether it pencils out.
It's the flagship of the Power Abundance suite because it unites the two threads — energy production and data — that define the case for orbital infrastructure.
Orbit sets an illumination fraction: geostationary orbit sees the Sun almost continuously, while low orbits spend a large fraction of each pass in Earth's shadow. Effective generation is your array's peak rating scaled by that fraction and its efficiency. You then divide that power between compute and downlink.
On-station compute turns almost all of its power into heat, so the station needs radiators sized to reject it at roughly 300 K — a constraint that often dominates orbital data-center design. Beamed power, meanwhile, loses energy at every step of wireless transmission, so delivered power is well below what leaves the array. Mass (thin-film array plus radiators plus structure) sets the number of heavy-lift flights, and capex combines launch and hardware. Levelised cost of energy and cost per GPU-hour then show whether the station competes with power and compute on the ground.
Put a 1,000 MWp array in geostationary orbit at 30% efficiency and send half its power to on-station compute: you get near-continuous generation, tens of thousands of GPUs, a large radiator to reject the compute heat, and a capex dominated by launch mass — making vivid why cheaper launch and lighter arrays are the two levers that decide orbital feasibility.
Space offers near-continuous sunlight and no land constraints; the catch is rejecting heat and the launch mass, both of which this tool sizes.
Thermal rejection and launch mass more than power — radiators to dump compute heat at ~300 K grow quickly with load.
Wireless power transmission loses energy at conversion, transmission, and rectification; the end-to-end efficiency input captures that.
Geostationary maximises sunlight but is far away; lower orbits are closer but spend time eclipsed. The tool shows the trade.
No — it's a transparent first-order model with adjustable public assumptions, for planning and education.
Yes — free, runs in your browser, and available in 25 languages.