Re-optimize battery & distributed-energy dispatch the instant prices or forecasts move — within the grid control-tick. The price signal and the forecast change continuously; a dispatch plan that arrives after the tick is already stale. PRISM returns a feasible, audited plan inside the deadline, changing only the few intervals worth changing.
Grid prices and forecasts move on a clock you don't control. The job isn't to find a beautiful schedule eventually — it's to return a feasible, audited dispatch the moment the inputs change, inside the control-tick, and to disturb only what genuinely needs to move.
Batteries, distributed energy resources, and virtual power plants live inside a market and a physical grid that never hold still. Prices update, forecasts revise, telemetry arrives — and each change can make the plan you're executing the wrong one. The window to respond is a control-tick, not a coffee break. Miss it and you're dispatching against conditions that no longer exist.
That turns dispatch into a hard real-time problem. The value isn't only in the quality of the schedule — it's in whether a feasible, defensible answer is on the wire before the tick closes. Conventional solvers can produce a good plan given enough time; the constraint here is that there isn't enough time, repeatedly, all day.
Each of these is manageable alone. Together, on a millisecond clock, they're why a plan that's merely "optimal eventually" doesn't help.
An answer after the control-tick is the wrong answer. The plan has to be feasible and on the wire inside the window — every tick, not on average.
State of charge, ramp limits, and commitments link the intervals together, so you can't re-solve one slot in isolation — the plan moves as a whole.
Re-writing the entire schedule every tick is operationally noisy. The plan should change only the few intervals genuinely worth changing.
You bring live inputs and a hard deadline; PRISM returns a feasible, audited dispatch plan inside it. The methods are proprietary; the interface is simple.
One engine, a hard deadline, deterministic.
Demonstrated results on the dataset described — not a guarantee. Comparators are referred to generically as conventional / standard solvers.
A feasible, audited dispatch plan delivered within deadlines from 500 ms down to ~5 ms — across the real-time range a grid control loop actually runs at.
The plan changed only the few intervals worth changing, rather than re-writing the whole schedule on every tick.
Every returned plan was feasible and audited — a defensible answer on the wire inside the window, every tick.
A matched-workload pilot on your prices, forecasts, assets, and deadline — a pass/fail metric you set before we start, every losing case shown.
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