Frequency Performance Payments were introduced into the NEM on 8 June 2025 to improve system frequency performance through financial rewards and penalties. The reforms also fundamentally changed the way FCAS Regulation costs are allocated across market participants.
WattClarity® has already published multiple articles on these changes – for example
Given that almost exactly a year has passed since the reforms were introduced, it seems like a good time to explore in detail how market participants have been affected. This article analyses the first year of FPP operation and quantifies its impact on utility-scale solar farms across the NEM between 8 June 2025 (the commencement of FPP) to 30 April 2026 (the latest data available at the time of writing).
The FPP reforms introduced two significant changes.
First, they introduced a new system of frequency performance payments. Market participants that contribute positively to frequency performance receive FPP rewards, while those that contribute negatively incur FPP penalties. This is a new pool of net-zero-sum rewards and penalties in which the total amount paid by “unhelpful” participants equals the total amount paid to “helpful” participants.
Second, the reforms changed how FCAS Regulation costs are allocated across the market. Previously, these costs were recovered through the Causer Pays framework. Under FPP, regulation FCAS costs are allocated using a new methodology that links cost recovery more directly to each participant’s contribution to frequency performance.
Frequency-related costs can be grouped into six categories:
FPP Reward
+
Payments received by participants that improve frequency performance
FPP Penalty
–
Charges incurred by participants that worsen frequency performance
FCAS Raise – Used
–
FCAS Lower – Used
–
Costs associated with lower regulation services that were actively used to correct frequency deviations
FCAS Raise – Unused
–
Costs associated with raise regulation services that were procured but ultimately not required
FCAS Lower – Unused
–
Costs associated with lower regulation services that were procured but ultimately not required
It is important to note that both FCAS regulation costs and FPP rewards or penalties are influenced:
While the new FPP framework applies to all market participants, the impact was not evenly distributed between generation types (percentages indicate % of total reward or penalty):
Solar farms accounted for 32.3% of all FPP penalties, despite contributing only 8.7% of total NEM generation over that period. While this appears to indicate an outsized penalty for solar farms, this is perhaps not entirely unexpected:
While the figure above shows total FPP rewards and penalties, each generation type provides significantly different amounts of generation. It is also helpful, therefore, to understand the FPP rewards and penalties per MWh for each technology:
As can be seen, battery storage obtains a high reward per MWh compared to other generation types, while solar incurs the largest penalty per MWh.
Across all utility-scale solar farms analysed [1], total FPP penalties amounted to $7.49 million, offset by $5.06 million in FPP rewards, resulting in a net cost of $2.43 million. The total frequency-related costs (sum of FPP and FCAS Regulation) amounted to $6.58 million for the period. Extrapolating linearly to a full year of operation, that would equate to $7.34 million for the first year of FPP.
To place FPP costs in context, net FPP represented 35% of total FCAS Regulation and FPP costs incurred by solar farms during the period analysed:
The introduction of FPP therefore significantly altered the composition of frequency-related costs faced by solar generators.
Total frequency-related costs averaged $0.38/MWh generated, equivalent to 1.23% of wholesale market revenue. However, this average masks substantial variation between regions, across seasons, and between individual solar farms.
FPP costs varied considerably month-to-month, with September to November having by far the highest costs:
This was partly due to higher average FCAS regulation costs during those months:
However, it seems that variable spring weather and cloud formation and patterns in those months played an important role as well.
The cost per MWh varied significantly from one solar farm to the next. The following graph shows individual cost for every solar farm:
For some solar farms, frequency-related costs per MWh were 3x as high as for others. One solar farm (Bolivar Waste Water Treatment solar farm) even managed to obtain a net reward of just over $5,000 across the year.
Notably, solar farms in New South Wales appear to mostly (but not always) have incurred higher costs relative to generation volume, while solar farms in South Australia appear to mostly (but not always) incur lower costs. Again, local weather conditions likely played an important role, with New South Wales and Victoria generally exposed to more variable weather than Queensland and South Australia.
The following chart shows costs incurred by solar farms outside of daylight hours, using timing of sunrise and sunset specific to every individual solar farm (percentage values indicate percent of total frequency-related costs – daytime plus nighttime):
It turns out that solar farms incurred total overnight costs of $1.47 million – representing 22% of all frequency-related costs. This may seem surprising, given that solar farms are presumably not participating in the market overnight. However, unused FCAS regulation costs are allocated using broader cost recovery mechanisms that apply to market participants irrespective of whether they are generating in a particular interval.
Does higher uptake of renewables lead to higher amounts of FPP? So far, that does not seem to be the case:
South Australia, with the highest renewable energy penetration, in fact experienced the lowest frequency-related costs per MWh generated.
To understand this well, it is helpful to look at FPP performance on two dates side-by-side.
Here is what they looked like:
On 18th April 2026, cloud-free skies led to highly predictable solar output, leading to stable frequency, and low regulation and spot prices.
On 3rd November 2025, on the other hand, much of south-eastern Australia was covered by cloud – partly thick cloud cover, and partly patchy, which leads to higher ramp rates and unpredictability for solar generation. This led to highly variable solar output, likely driving up FCAS requirements, resulting in higher FPP and FCAS costs. Wholesale prices in NSW1 and QLD1 in reached high levels later in the day, presumably due in part to cloud conditions over the course of the day.
It is worth looking at how individual solar farms compared on that specific day:
Interestingly, in some cases solar farms very close to one another had vastly different FPP outcomes, despite having been subject to very similar weather conditions and cloud cover. This suggests that operational decisions, too, have a big impact on how different solar farms fare when it comes to FPP, particularly on volatile days.
It is worth digging into the impact of cloud cover a little more deeply. Thursday 30th August 2025 also saw a day of high FPP costs for many solar farms in northeast New South Wales and southern Queensland. This is what cloud cover looked like on that day:
Long, stripe-like bands of low cloud (sometimes referred to as “cloud streets”) extended across eastern Australia. These conditions make it particularly difficult to forecast output (and set a dispatch target), and also make it particularly difficult to follow a steady trajectory to achieve a dispatch target. Cloud conditions such as these are therefore likely to be one of the biggest drivers of FPP (both rewards, and penalties) for solar farms.
A small number of dispatch intervals accounted for a disproportionately large share of both wholesale market revenue and frequency-related costs. More than 12% of all solar farm wholesale revenue was earned during just 0.22% of intervals, while 19% of all FCAS and FPP costs occurred during only 4.4% of intervals.
Several of the highest-cost events coincided with rapidly changing weather conditions, including sudden cloud formation and certain types of cloud patterns that caused significant deviations between actual and expected solar generation. These events demonstrate the strong relationship between weather-driven variability and frequency-related cost exposure.
FPP is now a significant component of frequency-related costs. Seasonality, location, and operational decisions all have a large impact on the frequency-related costs a solar farm operator must pay.
What does this mean for solar farms moving forward?
On the one hand, FCAS Regulation prices, a main driver of FCAS and FPP costs, appear to be broadly trending downward over the past several years.
On the other hand, extreme intervals can have a disproportionate impact on cost and revenue for the year. These are often driven by unique operating conditions that increasingly result from unexpected and extreme weather occurrences. In this context, accurate forecasts that have a high resolution (both in terms of time, and geospatially), are likely to become increasingly important – for both individual solar farm operational decisions, and to better forecast market-wide impacts.
For solar farms with co-located battery storage, these challenges and opportunities become even more significant. Operational decisions increasingly need to account not only for the next dispatch interval, but for market conditions over the coming hours and days. Given that more than 12% of annual solar farm spot revenue was earned in just 0.2% of intervals during the year, the ability to anticipate and prepare for rare but high-impact events is likely to become an increasingly important source of competitive advantage.
To follow from this article, Solstice AI has published a 28-page report ‘One Year of Frequency Performance Payments: Quantifying the Impact on Australian Solar Farms’ that readers can access here.
[1] A small number of solar farms were excluded from this analysis:
… meaning that typical performance is not representative of a standard utility-scale solar farm.
Solstice AI is an Australian technology company building the intelligence layer for a solar-dominated energy system. Headquartered in Melbourne, Australia, the company combines expertise in artificial intelligence, energy systems, and large-scale software engineering to deliver high-accuracy solar generation forecasts across utility-scale assets, distributed rooftop PV, and for entire regions.
Every solar farm is affected differently by Frequency Performance Payments. Solstice AI can help you understand your site’s exposure and evaluate how improved forecasting could reduce costs and improve market outcomes.
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