Queensland vs Victoria: Which State Delivered Better Battery Revenues in 2024?

Who’s the BESS’t, Queensland or Victoria?

Australia’s NEM is a zonal energy market, with pricing zones broadly aligned to State boundaries. As a result each State experiences different (but related) energy and ancillary services pricing. How do these different market conditions affect revenues for merchant batteries chasing market revenues?

To explore how location influences revenue outcomes, we modelled two hypothetical batteries in Gridcog, one in Victoria and the other in Queensland in 2024. 

Over the course of the year, the Queensland battery outperformed its Victorian counterpart by over $130k per MW, with Queensland total monthly revenues peaking at nearly $43k per MW in May and around $35k per MW in October. 

But why was Queensland so much more lucrative for batteries in 2024, and how do we know this is an accurate reflection of how battery assets performed in 2024?

Why was Victoria less lucrative in 2024?

Australia’s rapid growth in renewable capacity is increasing the value of flexible assets. 

When wind and solar generation are plentiful, these lower-cost sources push wholesale prices down, increasingly into negative price territory. But when renewable output drops then more expensive coal and gas units fill the gap, driving prices up. 

This volatility—often intensified by events like generator or network outages—creates strong opportunities for flexible assets like batteries to profit from wholesale arbitrage or to earn high revenues from providing grid support like frequency control.

Since each state operates its own spot market and has localised FCAS pricing, the value of these services can vary significantly across time and location. The graph below highlights this variability, showing the maximum intraday spread available to batteries in Queensland and Victoria.

As seen above, in 2024 Queensland had considerably more wholesale spot price volatility, leading to our Queensland modelled battery being able to capture more arbitrage revenue: ~$80k per MW more than Victoria over the year. 

Similarly, there were a greater number of high pricing FCAS events in Queensland, which led to higher FCAS revenues there for 2024. 

This is illustrated below showing breakdown of cumulative daily maximum FCAS prices for all FCAS market services  in Victoria and Queensland.

But how do we know our modelled assets are accurate, and that if they were market participants in 2024, that they would experience similar financial outcomes? 

How accurate is Gridcog modelling?

Gridcog enables users to accurately model BESS revenue performance against historical market prices and against long-term price projections for wholesale energy markets, capacity markets, and ancillary service markets.

We regularly benchmark Gridcog against real-world asset performance to validate accuracy and to provide guidance to users on how to configure parameters in their Gridcog models. 

We provide full details of this benchmarking to Gridcog users, but we’ve shared some high-level information for Victoria and Queensland below.

As seen above, our Gridcog modelled scenario’s normalised revenue closely aligns with the actual assets financial performance for both Victoria and Queensland. 

However, there are a few months where there are noticeable differences, February in Victoria, and October in Queensland. So why the divergence? 

On February 13th in Victoria, there was an extreme weather event which caused multiple generators, loads and transformers to trip, which as a result, sent wholesale prices to over $16k per MWh. 

During this event the actual BESS asset we were benchmarking against did not discharge to capture revenue, whereas the Gridcog modelled asset did, earning higher wholesale arbitrage revenues. 

We’ve shown an excerpt from our Gridcog benchmarking project model below with the discharging and charging profile for an actual Victorian BESS asset we were benchmarking against on February 13th. You can see that it missed the wholesale price spike, which our modelled battery was able to capture.

The story in Queensland was similar, but was more driven by FCAS rather than the spot market. There were 15 occasions in October where the 30-minute FCAS price for the R6 market exceeded $5,000 per MW, due to, in part, planned outages during which Queensland was required to provide its own local FCAS. 

For the purposes of our benchmarking, we prioritise simplicity and transparency, so we configured Gridcog with a single, simple NEM-wide assumption regarding the percentage of offered FCAS capacity that would clear in the market over the year (noting Gridcog users can configure their own more granular pricing zone level, time-of-year based, FCAS service specific, or project/asset specific assumptions on average offered capacity accepted by the system operator).

Because of this underlying assumption for FCAS volume clearance, our modelled battery cleared much lower volumes during the October high-price events in Queensland, leading to the Gridcog modelled battery underperforming compared to the actual asset analysed (noting that despite this, the total 2024 revenue for the Queensland Gridcog modelled battery was still within 2.9% of our benchmark).

Conclusion

The markets batteries operate in can significantly impact project returns. For battery asset developers, the ability to simulate and value assets in different locations experiencing different market conditions is essential to designing a bankable project that will deliver great returns.

Gridcog lets users simulate real market dynamics, explore project design options (like hybridisation), and compare commercial structures to identify the most valuable path forward. Get in touch to see how we can support your project modelling needs.

‍