The Foresight Tax

The way most people underwrite battery storage is wrong. Not slightly wrong — structurally wrong. And I think the next two years are going to make that very visible.

A disclosure up front: the voice on this episode isn’t my organic voice. It’s an ElevenLabs clone reading a script I wrote, in conversation with a synthetic co-host named Cera. Treat it as a collaboration between me and the tools.

The provocation

There’s a number that gets quoted in almost every battery investment deck I’ve seen in the last five years. It’s the result of a perfect-foresight backtest. You take a battery. You take a year of historical electricity prices. You ask a computer: “if you had known the prices in advance, what would you have earned?” The computer gives you a beautiful number. The deck quotes that number, applies a small haircut — ten percent, maybe twenty — and calls it the base case.

That base case is fiction. Worse, it’s a specific and measurable kind of fiction. It assumes the operator can see the future.

I’m calling the gap between that omniscient number and reality the foresight tax. The metric isn’t mine — AEMO and ARENA in Australia have been quietly inventing the vocabulary for the last year. But the practical implication needs to be said louder than they’ve been saying it: a material fraction of the merchant battery debt issued in the last five years is mispriced.

The German study

The cleanest evidence comes from a 2025 paper on the German continuous intraday market. One-hour battery, full year of 2023, three cases:

* Perfect foresight on continuous intraday: €164,400. The oracle benchmark.

* Forecast-based continuous intraday: €146,237. Real software, real forecasts, real execution friction. Eleven percent below the oracle.

* Day-ahead only: €40,590. About a quarter of the oracle.

Same battery. Same year. Same market. The difference is entirely the information set the strategy uses.

That gap between case two and case three — €146k versus €40k — is the value that lives in intraday repositioning. In the option to change your mind when better information arrives. A day-ahead-only strategy buys early commitment and burns optionality. If a battery deal pitches you with pure day-ahead arbitrage in the model, you should already be suspicious.

What AEMO actually said

AEMO — the Australian Energy Market Operator — has been doing something quietly significant. Their long-term planning models used to assume perfect foresight for storage dispatch. They started comparing model output to what real batteries actually did in 2023 and 2024. There was a gap. Real batteries discharged differently. Real batteries left charge in the tank. Real batteries hit their daily maximum discharge in the evening peak window, even when, with hindsight, there was a better window earlier in the day.

AEMO now uses what they call imperfect-energy-target modeling, with small headroom and footroom reservations. Their own testing shows the imperfect model gets closer to actual battery behavior than the perfect-foresight one did. ARENA put it more bluntly in a recent paper: perfect foresight is becoming a “material simplification” because storage decisions depend on uncertain future prices and imperfect knowledge of future system conditions.

When the agency that funds renewable storage research says your benchmark is materially wrong, you have to listen.

The South Australia incident

5 April 2024. Higher-than-normal morning prices in South Australia. Some batteries decided to discharge early to capture those morning prices. Reasonable decision. The forecasts said the day would normalize. So they monetized.

Then an unplanned outage hit. The spot price went to AUD 9,899 per megawatt-hour at 7:30 in the morning. One battery entered that interval with 14% state of charge. They had nothing left to sell into the spike — the biggest spike of the day, maybe of the year.

A perfect-foresight backtest would have nailed it. The backtest knew. The operator did not. And no amount of better forecasting would have helped, because the spike was triggered by an unplanned outage. The information genuinely did not exist before it happened.

The lesson is not “buy better forecasting.” The lesson is design for the world where you cannot know.

The metric

Formally: foresight tax = 1 − (settled profit / perfect-foresight profit). Same battery, same year, same realized prices, same physical constraints, same settlement rules. Two information sets — the strategy under uncertainty, and the oracle.

There’s a second metric I find more useful in negotiations:

Option Preservation Ratio (OPR) = (settled profit − day-ahead-only baseline) / (oracle − day-ahead-only baseline).

This measures how much of the gap between dumb and omniscient your software actually closed. In the German example, the forecast-based intraday strategy had an OPR of about 85%. That’s a real number. The kind of number you can actually pay a software vendor for.

If a battery optimizer charges you 20% of revenue and their OPR is 85%, the fee is justified. If their OPR is 60%, the fee is parasitic. Today most procurement is “what’s your revenue share?” — treated as comparable across vendors. It is not.

The architecture that follows

If the moat is option preservation under uncertainty, the architecture follows. Forecasting in the cloud — fine, the cloud knows more. Portfolio optimization in the cloud — fine. Execution at the edge — non-negotiable.

Australia’s fast FCAS uses 50-millisecond measurements. NESO dynamic services in Britain require 1-second or 10-second response. ISO New England regulation follows 4-second AGC signals. Cloud APIs respond in 2–5 seconds. There is no architecture in which a cloud-only stack participates in the fast products. The math doesn’t allow it.

That’s why I built Sourceful around a $99 gateway running our software in the building. 200ms response. Protocol agnostic. Works offline. Not because edge is fashionable — because the markets that pay for fast batteries clear at speeds the cloud cannot reach. Either you control the milliseconds or your foresight tax is set by your hardware vendor’s firmware update schedule.

Three takeaways

For investors. Throw out perfect-foresight underwriting. Demand non-anticipative backtests. Demand option preservation ratios. If somebody pitches you a battery deal with a perfect-foresight backtest and a token haircut, pass.

For utilities. You are in the catbird seat if you understand this. Write market rules that reward option preservation. Require non-anticipative bidding behavior in prequalification. Prioritize fast products like mFRR over static reserves — Svenska kraftnät is showing the way with their September 2026 cap on static FCR-D.

For C&I battery owners. Don’t underwrite on merchant arbitrage alone. Anchor on tariff savings and contracted host-load value. And ask your optimizer for their foresight tax. If they don’t know what that is, find another vendor.

The reckoning

There’s a small reckoning coming. Not catastrophic, not systemic. Just the normal kind of correction that happens when an industry matures and people stop pretending the model and the reality are the same thing. Good operators will be fine. Good optimizers will be fine. Serious lenders will be fine. Everyone else has to learn.

The grid is becoming a distributed computer. The asset that matters most is the one that knows it cannot see the future, and plans accordingly.

Key Takeaways

* Perfect-foresight backtests overstate battery value by anywhere from 11% to 75% depending on the strategy. AEMO and ARENA are now officially saying so.

* The German 2025 study quantified it: oracle €164k, forecast-based intraday €146k, day-ahead-only €40k. Same battery, same year, same market.

* Foresight tax = 1 − settled/oracle. Option Preservation Ratio = how much of the gap between dumb and omniscient your software actually closed. OPR is the metric you should be negotiating optimizer fees on.

* The architecture that minimizes the foresight tax is split: cloud for forecasting and portfolio optimization, edge for execution. Cloud APIs cannot meet the 50ms–1s deadlines that fast frequency markets impose.

* Sweden’s BRP/BSP split (May 2024), EIFS 2025:1 metering reform, and the September 2026 FCR-D static cap are all pushing toward the same architecture.

* A material fraction of merchant battery debt underwritten on perfect-foresight backtests will get repriced as the vocabulary spreads. The base case should be a non-anticipative, settled, friction-aware backtest. Perfect foresight belongs in the appendix.

Full transcript available below the audio player.

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