US battery storage developer and long-term management firm Spearmint Energy is “a little bit distrustful” of the “black box” of optimisation, its head of trading told Energy-Storage.news.
Battery storage projects are increasingly set to move away from solely providing contracted ancillary services – the bulk of revenues in most markets outside California – and towards energy trading, capacity markets and other revenue streams.
This is largely down to a saturation of those ancillary service markets by batteries as deployments grow. Energy-Storage.news has written about this extensively, most recently in ERCOT, Texas, and Europe but the trend is expected in the UK too.
This change means a rise in the complexity of optimising battery storage projects and what revenue streams they tap into over the course of a day to maximise returns. That in turn has led to substantial growth in the third-party optimisation space, where day-to-day management of batteries’ discharge is outsourced to specialised outfits or large players’ digital services. These often use artificial intelligence (AI) based algorithmic trading strategies.
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However, Nick Dazzo, head of trading at developer Spearmint Energy, was sceptical of the rationale of outsourcing management of a battery storage fleet to an AI-based solution.
Speaking to Energy-Storage.news whilst at Energy Storage Summit USA last month, Dazzo said: “With optimisation, I think most in the industry would describe it as something of a black box. At Spearmint, we are a little bit distrustful of that because we don’t think a black box is the best way to deploy our investors’ resources.”
The firm develops battery storage projects, starting with some 1GW it has recently acquired in Texas, but also provides long-term management of whole battery storage projects to investors looking to transfer risk onto a third-party.
“We will have battery trading performance that needs to be explained in terms that investors can understand,” Dazzo continued.
“It would be unacceptable to simply point to someone else’s algorithm and hope that that can answer their questions. We need to be able to explain our performance in very fundamental terms.”
“Trading in the ERCOT market requires real-time decision making that gets overcomplicated by the notion of optimisation. Some in the industry suggest that all of this can be handled by algorithms, but in our view some aspects of trading are unknowable. You cannot be proactive about everything; you have to react, you have to make decisions, and that to me is an important aspect of trading.”
Julian Nebreda, CEO of battery storage system integrator Fluence which has also expanded its third-party management services segment, recently said in a podcast with Aurora Energy Research that all-but-the-largest companies will probably need to outsource management of their battery storage long-term.
The role of AI in optimising battery storage revenues was also discussed at the Energy Storage Summit EU in London a month prior to the US event. Eku Energy’s head of technologies EMEA Andy Hadland reckoned that scaling up may actually make it harder to manage batteries without AI-based optimisation.
Read more Energy-Storage.news reporting on the topic of optimisation in battery storage here.
