Product · Methodology

How Flexgy decides, and when it does not

Four steps in order, each with an explicit threshold. If any of them fails, the decision falls back to the DSO’s conservative physical rule.

  1. Calibrated margin

    Flexgy measures how wrong your engine has been in the past at that node and under which conditions. From those errors it computes a margin for the risk level you choose (P50 to P99), instead of a fixed figure for every case.

    Technique: conformal prediction on the engine’s errors.

  2. Never-seen state

    The margin only holds if the grid resembles the calibration period. Flexgy measures how far the current state (temperature, demand, generation, topology) is from anything it has seen. If it is too far, it does not trust the margin.

    Technique: out-of-distribution detection with a threshold set in advance.

  3. Physics check

    Before recommending anything, the limit is checked against the security criteria: thermal loading of the elements, voltages within limits and the N-1 criterion.

    The same criteria set by the POD1 operating procedure.

  4. Decision and record

    If everything passes, it acts. If confidence falls short, it limits just enough. If the state is new or the physics does not close, it abstains and applies the conservative rule. In all three cases an Evidence Passport is produced.

    Fixed, versioned rules, not judgement of the moment.

The four steps on one screen: the engine candidate, the calibrated band, the never-seen state and the recorded decision. Illustrative screen with synthetic data.

Assumptions and limits, in writing

  • Calibration assumes the future resembles the recent past. That is why step 02 exists: when it does not, Flexgy says so and steps aside.
  • Flexgy does not fix a poorly modelled engine: it detects it, because its past errors widen the margin.
  • Abstaining is not a failure: it is the right answer when there is not enough evidence. It is measured and reported.
  • The risk level is chosen by the DSO, not by Flexgy.

How it is measured

The metrics we agree before every pilot, with success and stop criteria.

False-safe decisions
Times a limit was authorised that reality would not have withstood. This is the metric that rules.
Capacity utilisation
How much flexible capacity is used compared with a fixed margin.
Abstention rate
How often Flexgy falls back to the conservative rule, and why.
Calibration
Whether the chosen risk level holds in practice (e.g. P95 ≈ 95 %).
Latency
Decision time, compatible with real-time instructions.

Status

The methodology is implemented and validated on synthetic data. Figures on a real grid will only exist after a pilot, and we will publish them with their context.

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