Fair Curtailment
Overview
Periods of surplus occur when the electricity system contains more available generation than can be safely transported, consumed or exported.
This may arise because:
- renewable generation exceeds demand,
- export capability has been exhausted,
- local network constraints prevent additional injections,
- voltage or thermal limits have been reached, or
- system security requires generation to be reduced.
Under these conditions, not every generator can export its full available output.
A decision must therefore be made about which generators should reduce their production.
Fair Curtailment is the component of Fair Play responsible for making these decisions.
Surplus is a Physical Constraint
Surplus is not caused by market design.
It is a consequence of the physical limitations of the electricity system.
The Automatic Market Maker continuously adjusts prices to encourage additional demand, storage charging and other forms of flexible consumption that can absorb surplus generation.
In many situations these price signals eliminate the surplus entirely.
Only when the network reaches its physical operating limits does Fair Curtailment become active.
Like Scarcity Allocation, Fair Curtailment is not an alternative to market pricing—it is the mechanism used when prices alone can no longer resolve the imbalance.
Curtailment is Sometimes Unavoidable
Modern electricity systems increasingly rely upon variable renewable generation.
There will inevitably be periods when more renewable energy is available than the electricity system can accommodate.
Examples include:
- exceptionally windy conditions,
- high solar output during periods of low demand,
- local export bottlenecks,
- temporary network outages,
- maintenance activities.
When these situations occur, some generation must be reduced to maintain the safe operation of the network.
The challenge is no longer whether curtailment should occur, but how it should be shared.
Preserving Economic Efficiency
Fair Curtailment does not determine the dispatch schedule.
The Automatic Market Maker first identifies the economically efficient and physically feasible operating point.
Where multiple equivalent curtailment decisions remain, Fair Curtailment determines how the required reductions should be distributed.
Fairness therefore operates only after:
- prices have been determined,
- network feasibility has been established,
- economically efficient dispatch has been identified.
This ensures that fairness complements optimisation rather than replacing it.
Sharing the Burden Fairly
Repeatedly curtailing the same generator creates poor investment incentives.
Over time it would discourage investment in locations that may otherwise provide significant value to the electricity system.
Fair Curtailment therefore distributes unavoidable curtailment across participants in a transparent and predictable manner.
Generators that have historically experienced greater levels of curtailment gradually receive increased priority during future surplus events.
Conversely, generators that have consistently exported without interruption become marginally more likely to contribute when additional curtailment is required.
The burden of surplus management is therefore shared across repeated market interactions rather than concentrated on the same participants.
Fairness Over Time
Like Scarcity Allocation, Fair Curtailment evaluates fairness across many market intervals rather than within a single event.
Each generator accumulates a fairness history describing the proportion of its available generation that has historically been accepted.
Generators that have experienced comparatively low acceptance become progressively less likely to be curtailed in future.
Those with consistently high acceptance become slightly more likely to contribute when further curtailment is required.
This creates a self-correcting feedback mechanism that continuously balances curtailment across the market.
Probabilistic Curtailment
Where multiple generators represent equally acceptable candidates for curtailment, Fair Curtailment uses probabilistic selection rather than deterministic priority lists.
The probability of curtailment depends upon:
- historical acceptance,
- contractual obligations,
- physical feasibility,
- current network conditions.
This approach prevents persistent curtailment of individual participants while remaining adaptable as generators enter and leave the market.
Over time, curtailment naturally becomes more evenly distributed without requiring manual intervention or arbitrary rotation schedules.
Supporting Efficient Investment
One of the objectives of Fair Curtailment is to preserve confidence in long-term investment.
Developers need confidence that unavoidable curtailment will not be imposed disproportionately on a small subset of participants simply because they were connected first or happen to occupy a particular network location.
By distributing unavoidable curtailment fairly over time, FP-AMM creates more transparent and predictable operating conditions while still respecting the physical limitations of the electricity system.
This improves the long-term investment environment without compromising network security.
Example
Consider a region containing several wind farms connected to the same transmission corridor.
A period of exceptionally strong wind causes available generation to exceed the export capability of the network.
The Automatic Market Maker first identifies the economically efficient operating point and determines the amount of generation that must be reduced.
Several wind farms are equally suitable candidates for curtailment.
Rather than repeatedly reducing output from the same facility, Fair Curtailment considers each generator's historical acceptance record and probabilistically distributes the required reductions.
Over successive surplus events, generators that have previously experienced greater curtailment become progressively less likely to be selected again, ensuring that the burden is shared fairly across all participants.
A Symmetric Design
Scarcity Allocation and Fair Curtailment are two expressions of the same underlying principle.
During scarcity, Fair Play determines how limited energy or network capacity should be shared between consumers.
During surplus, Fair Play determines how limited export capability should be shared between generators.
The direction of the resource flow changes, but the fairness objective remains identical:
No participant should repeatedly bear a disproportionate share of unavoidable system imbalance.
This symmetry allows a single fairness framework to operate across both sides of the electricity market while maintaining transparency, consistency and predictable behaviour.
Next
The next section introduces Fairness State, which explains how FP-AMM maintains a memory of previous allocation outcomes and uses this information to balance fairness across repeated market interactions.