OptiGrid CEO on battery storage optimisation

Battery storage warranties and long-term service agreements can distort trading behaviour if optimisation platforms fail to account for them properly. This is according to Sahand Karimi, CEO and co-founder of Australia-headquartered optimisation software firm OptiGrid, in an interview with ESN Premium.

Karimi argues that capturing a battery's full value requires an optimiser capable of accounting for offtake obligations and other constraints. He says the underlying issue extends beyond any single project's commercial terms. "All batteries have warranties and long-term service agreements that they need to take into account when you're optimising their trading," Karimi states. He warns that unintegrated constraints can lead to "weird outcomes."

He points to a price cap event in South Australia on 21 June 2026 as an example. Prices in the SA1 region hit the National Electricity Market's cap of AU$20,300/MWh twice in one evening. The state's fleet of grid-scale batteries captured a combined AU$324,000 in revenue, but performance varied sharply between individual assets.

Karimi previously told ESN Premium that this divergence came down largely to state of charge management and bidding strategy, not raw capacity. Some assets captured meaningful revenue while others were caught charging into the price cap itself.

Autonomous optimisation over manual override

Karimi is direct about operational philosophy, arguing against a model where human traders periodically disable automated optimisation to intervene manually. "We don't think the optimal way to operate the battery is to turn off the optimiser and then do manual bidding and then turn it back on," he says.

Instead, he describes an approach where human input shapes the parameters within which an optimiser operates. "What's optimal is that you allow the human trader operator to input their preferences, their constraints, their objectives, and then the optimiser should automatically take those into account and then optimise the revenue within those bounds," Karimi explains.

He notes OptiGrid's platform, OptiBidder, allows traders to adjust the optimiser's behaviour. The design keeps the algorithm running continuously rather than ceding control entirely during manual adjustments. This constraint-aware, always-on optimisation is presented as a key lever for closing the gap between a battery's theoretical earning potential and its actual captured revenue.

A six-month onboarding runway

Asked about lead times for optimisation planning before a project goes live, Karimi sets out an internal benchmark. "From our perspective, we need at least six months ahead of the go-live," he says. This window covers integration work with a project's SCADA control system and setting up the trading strategy.

During this period, the optimiser runs in a digital environment. Human traders can observe its performance and test strategies before the asset begins real trading. Karimi says OptiGrid has worked to shorter timelines, but more lead time generally produces a better outcome. "The more time we have, the better, in the sense that we can make sure that we've ticked all the boxes," he notes.

Managing correlation and cannibalisation

When asked how OptiGrid mitigates the risk of correlated dispatch as its network of optimised assets expands, Karimi argues the risk is manageable. He says optimisation outcomes depend on each asset owner's specific constraints and objectives, not solely on shared market forecasts.

"Even with the same price forecast, even with the same market forecast, the behaviour will not necessarily be the same because they're following different objectives," Karimi explains. He notes OptiGrid has observed this directly within its portfolio, where optimal bids differ based on how each asset's optimiser is configured during onboarding.

Karimi also discloses a second product in development called OptiTrader. This is a portfolio-level optimisation and risk management layer designed to sit above OptiBidder. It is intended for asset owners managing multiple battery storage assets in a single market.

"That's for companies that have portfolios of assets, ensuring that each asset will not cannibalise the revenue from the other," he says. He distinguishes this from cross-owner correlation risk. Assets under different owners have different constraints and strategies, making identical behaviour less likely. Assets under common ownership, however, face a higher risk of similar, self-cannibalising dispatch behaviour, which OptiTrader is designed to address.