How a Renewable Operator Puts a Price on Every Megawatt Already Tracked

Market Strategy puts a euro sign on every megawatt a renewable operator already tracks, so settlement stops being accepted at face value and commercial decisions stop being made in megawatts alone.

Challenge

Most operators see two numbers: the megawatts their forecast predicted, and the euros on the offtaker's invoice. What sits in between - whether the invoice itself is correct, and whether the offtaker actually made the best commercial call on the site's behalf - stays invisible. A deviation shows up as one monthly cost figure, with no way to tell whether it came from a forecast miss, a declared unavailability, an underperforming asset, or how the offtaker chose to redistribute and dispatch that day.

The goal was threefold: verify every invoice line independently before accepting it, verify the offtaker's market decisions against the best achievable outcome on the same real prices, and trace every euro of imbalance back to the one step that actually caused it.

What we built

Market Strategy runs on the same hub that already holds programmes, declarations, production and settlement data - adding market prices is what unlocks all three checks:

Settlement verification - each invoice line is projected independently from our own data before the offtaker's invoice arrives, then reconciled line by line once it does, so a variance is caught as a query, not accepted as a given.
Strategy validation - the offtaker's actual commercial decisions are compared against the best achievable outcome on the same real settlement prices, answering not just "was the invoice correct" but "was it the right call" - stay on the market or step away from it, sell day-ahead or hold for intraday, bet on an ancillary-service payout or trade normally instead.
Loss traceback - every euro of imbalance or ancillary loss is split by origin - forecast error, availability and unavailability, redistribution and interconnection capping, or a specific commercial decision - per site, per month.

Results

EUR 9.5k of variance on one month - three query-worthy invoice lines alone, caught before they became a dispute: an intraday session settled at the wrong price, a declared limitation charged as deviation, and an ancillary revenue split taken before the management fee instead of after.
A repeated offtaker decision, tested against real settlement outcomes - one operator's offtaker had been taking a plant physically off the market on weekends, betting on an ancillary-service request to reconnect it instead of trading normally. Checked case by case against real invoices and settlement prices across eight confirmed weekends, the bet lost money overall: a net impact of roughly EUR -9,000, driven mostly by lost renewable-certificate revenue rather than low market prices, since the certificate rate is fixed regardless of price. Three of the eight weekends got no ancillary-service compensation at all, losing more on their own than the total loss across the whole sample - a pattern invisible from the invoice alone, and only visible once each disconnection was priced against what normal trading would have settled for, including the imbalance risk normal trading would also have carried.
Every loss traced to one of four causes - across plant configurations, monthly losses split cleanly by sub-plant: forecast error and availability dominate some configurations, while redistribution, capping and specific commercial decisions dominate others - each site carrying only the categories that actually apply to it.

Impact across the organisation

Settlement stopped being something the offtaker's invoice determines and became something checked against an independent, line-by-line projection - validated to the cent against real invoices before being trusted for anything else. Commercial decisions stopped being judged only on whether they looked reasonable in the moment and started being judged on their real settled financial outcome, against the same real prices anyone could have traded on - including recurring offtaker decisions that seem fine case by case but only reveal their true cost once every case is added up. And a monthly loss figure stopped being a number to explain away and became a diagnosis - forecast, availability, redistribution, or a specific commercial choice - that points straight at what to fix next.