Engineering and automotive plants run multi-shift operations with test benches, paint lines, robotics and a growing fleet of EV charge points. The load profile is predictable but expensive — and every new charge point shifts it further. EXAIOS works out the most profitable combination of PV, storage and load management for exactly that profile.
Steady production load across two or three shifts, overlaid by paint-line and test-bench peaks and increasingly by plant and staff charging infrastructure. The demand charge rises with every new charge point — often without anyone having computed how it interacts with the grid connection.
How much PV on hall roofs and car parks pays off for self-consumption? Does storage buffer the charging infrastructure instead of reinforcing the grid connection? When does the connection become the binding limit? EXAIOS evaluates charge management, PV and storage together rather than in silos.
Six coupled dimensions — generation, storage, consumption including charging, grid connection, market and economics — yield one dominant architecture with the lowest lifecycle energy cost. Peak shaving, self-consumption and charge control flow together into both the sizing and the cash flow.
You see IRR, NPV, DSCR and the p10 cover per site — plus an honest NO-GO when an expansion does not pay off. Instead of an invented example figure, you compute your real site in minutes.
EXAIOS returns the decisive figures for every site:
We publish no invented numbers. Compute your real site in minutes — the first indication is free.
Start a free indicationOften more cheaply than reinforcing the grid: the battery buffers charging peaks so the existing connection suffices. EXAIOS computes both routes against each other.
Frequently yes — carport PV raises self-consumption and feeds the charge points directly. EXAIOS evaluates roof and parking areas together.
Yes: deterministic, reproducible, backed by DSCR and p10.