Battery and storage dispatch, demand response and DER coordination. We turn a built asset into an optimised one — modelling-led control that captures value in real markets, not just on paper.
A battery that charges at the wrong hour. A generator that ignores the price curve. A fleet that all draws at once. The hardware can be flawless and the value still leaks away in the schedule. Optimisation is the discipline of making the right move at the right moment — across a single asset or a whole portfolio — so the physics you paid for actually shows up in the numbers.
“Dispatch is a design choice. The same asset, run well or run blind, produces very different numbers.”
Capture the asset, its constraints and the market it trades into.
Prices, demand, generation and state-of-charge — with uncertainty built in.
MILP and linear programming compute the value-maximising schedule.
Execute through real-time control, closing the loop with the asset.
Measure against the optimum and tighten the strategy over time.
Optimisation that turned built assets into better-performing ones.
Shifting compressor and generation load to follow day-ahead prices — turning a flat setpoint into price-aware, optimised operation.
View project →Real-time detection and dispatch of distributed batteries for per-cycle frequency support — the backbone for demand response and load control.
View project →Charge control across 30+ parks in six countries — scheduling a whole fleet within the grid connection it already has.
View project →Wavelet decomposition to dispatch a large, mixed generation fleet in milliseconds — accurate enough to run on modest hardware.
View project →Advisor is our energy monitoring and measurement & verification product — it turns metering data into dashboards, alerts and verified savings. Energy Asset Optimisation is the engineering that decides how assets actually run: battery and storage dispatch, demand response and control. One measures and verifies; the other optimises and acts. See Advisor →
No. We design for uncertainty — using robust and predictive methods that derive structure from the price signal itself rather than relying on a single perfect forecast, so the schedule holds up when reality diverges from the plan.
Yes. We optimise from a single battery up to a coordinated fleet of distributed energy resources — portfolio dispatch and VPP-style aggregation that treats many assets as one controllable resource.
Degradation is built into the optimisation objective. We cycle for value net of wear — degradation-aware dispatch that weighs each cycle's revenue against the life it costs the pack.
Dispatch, storage and control — value captured in real markets, across one asset or a whole portfolio.