Two grid-side factors help determine the return but are often ignored: the structure of grid fees, and the risk of being curtailed during network congestion. Anyone who leaves them out is planning with revenue that never arrives.
Demand charge and energy price, atypical grid usage and § 14a change effective network cost considerably. The right architecture actively lowers it — the wrong one cements it for 15+ years.
PV and feed-in projects can be curtailed during network congestion. Every kilowatt-hour that cannot be fed in is lost revenue. A return that does not subtract the expected curtailment is set too high.
EXAIOS prices expected curtailment and grid-fee structure into the cash flow — not into a footnote. That way the return rests on kilowatt-hours that can actually be sold.
In networks prone to curtailment, a battery that stores surplus generation can turn the risk into revenue. EXAIOS tests whether and how that pays off.
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 indicationStrongly network-dependent. EXAIOS evaluates the expected curtailment site by site and subtracts it from the revenue.
Often yes — by storing instead of feeding in during congestion. EXAIOS computes whether that pays off.
Because at many industrial sites the demand charge is the largest cost block — and it can actively be influenced.