This third article in our four-part series examines the first year of settlements, including which technologies were paid and which paid into FPP and whether the new arrangements appear to be changing behaviour.

High level settlement patterns

FPP-Reg-FCAS Recovery’s purpose is to calculate errors by unit and charge for them. Whilst there are differences in settlements for units of the same class, (covered later in this article), settlements have largely followed a pattern by scheduling category. Scheduled units have generally implemented MPFR, usually have controllable energy available to respond, and may be enabled for Regulation FCAS so AGC can move them in the correcting direction. For these reasons, their deviations are often classified by FPP as good.

Frequency Performance Payments including changes to Regulation FCAS cost recovery were introduced in July 2025. The following chart provides the settlements by scheduling category, with Semi-Scheduled Generators paying into FPP on a net basis.

The revised FCAS cost-recovery arrangements have also made cost allocation sharper for the poorer performers under FPP: wind, solar and residual errors, with the residual category largely representing forecast error.

Semi-scheduled wind and solar farms are more often bad because of the variability of their energy source, although some units in the cohort will usually be good at any point in time, and some may have implemented MPFR to also help. A wind or solar farm complying with MPFR may need to curtail generation to be able to respond, and even then may suffer variations in resource availability that can “swamp” good primary response for small deviations in frequency. Residual deviations are also usually bad, because the system cannot be controlled through uncontrolled elements that must be forecast. The following chart groups errors into scheduled units, semi-scheduled units and bidirectional units (BDUs), with semi-scheduled units mainly comprising wind and solar farms, and BDUs being batteries.

The chart follows the format of the preceding ones in Article 2, with errors stacked, and then relevant metrics, RCR, Regulation enablement and usage – which are shown on the same side as the good deviations – because this is the side that they should be expected to be on.

This pattern in one hour’s data extrapolates into broader patterns that explain the settlement transfers.

Incentives and participant behaviour

Participants can compare the marginal price of dispatch errors with the regional reference price, LGC prices and their own operating costs when deciding whether to limit dispatch, improve output control, or offer into Regulation FCAS so AGC can control the unit and potentially improve FPP outcomes. At the rates shown in the Article 2 examples, it is questionable whether negatively priced offers submitted by solar and wind farms, which reflect the opportunity cost of a Large Generation Certificate (LGC) under the Renewable Energy Target, remain profitable if, at the margin, incremental generation incurs FPP and Reg-FCAS Recovery costs. A unit may be better off submitting higher offer prices, foregoing some energy dispatch and following the scheduled dispatch instruction.

Semi-scheduled generators

Here are the top semi-scheduled generators over 2025–2026. What is evident is that the worst performers are those with high FPP debits, which also carry a liability for unused FCAS through DCFs. Some of the best-performing units seem to avoid FPP settlement almost entirely, meaning they may be quite successfully following targets.

 

Bidirectional units

Here are the top BDUs. This time, the period has been reduced to June 2026 because many of these BDUs are very newly commissioned. These units’ payments are dominated by Regulation FCAS revenues. However, they also receive FPP credits, but in doing so do not always avoid FPP debits or a share of unused costs, which would indicate that at times AGC signals and FPP’s Frequency Measure are at odds with each other. This is discussed in the next article.

An interesting outlier is Waratah – WTAHB1. Although registered for FCAS, it does not appear to sell Regulation FCAS, yet it performs very well under FPP. Its strong FPP performance may reflect an aggressive droop setting. That strategy differs from other units and may not be optimal: with aggressive droop, the plant responds to small frequency deviations and therefore incurs dispatch errors regardless. By offering Regulation FCAS instead, it could largely control dispatch errors in either direction, receive AGC signals that at times create good deviations, and be paid the FCAS price when enabled.

Scheduled generators

Here are the top Scheduled Generators, this time the period has been extended back to the full year to 2025-2026.

The worst performers, with Gladstone and Vales Point being the obvious standouts, compare poorly to equivalent coal-fired thermal stations. This would suggest that these units are operating at different droop settings than those specified in MPFR, have derogations against the requirement, or are frequently operating in a mode without primary (droop) control.

Overall

FPP-Reg-FCAS Recovery appears to have delivered on its core purpose: measuring dispatch errors, pricing their correction, and creating transfers that support more efficient dispatch and frequency control.  Although the general settlement patterns are from semi-scheduled plant and the residual to scheduled BDUs and generators, semi-scheduled generators vary. This suggests plant operators and traders can optimise these costs which may be driven by different operating controls and revenue streams where the trade-off between on maximising dispatch over reducing dispatch errors may differ.

The new FPP data also provides a richer view of how dispatch errors arise and how effectively Regulation FCAS corrects them. This is the focus of the next and final article.

 

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