Probabilistic Energy-storage Assessment.
Make every battery hour earn, without using up its life.
An optimiser that plans a battery's state of charge across every simulated hour, stacking arbitrage, frequency response and balancing revenue while pricing in efficiency losses and wear.
Why it matters nowA battery only pays back if it is sized and run against the real prices and congestion at its node. Too big and capital sits idle; too small and value is left behind. PEA finds the size and the strategy that pay back.
How PEA works.
- 01
Multi-period SoC
One half-hourly optimisation covers arbitrage, frequency response and balancing bids together.
- 02
Stochastic scenarios
All simulated hours of price and frequency, stored in Parquet for sub-minute access.
- 03
Degradation-aware
Round-trip efficiency and cycle/calendar ageing priced into every dispatch decision.
- 04
Value-stack output
A revenue stack and a battery-life forecast a lender can work with.
Charge cheap, discharge into the peaks.
A representative day of optimised dispatch: state of charge follows the spot price, with charging and discharging windows shaded.
Figures from an example run on a test network.
Value-stacking lifts revenue +135% over arbitrage alone, and PEA shows it can be done without wearing the battery out early.