How the control algorithm works
Operating decisions made in real time that tilt the plant toward the cheapest energy without compromising the process. Every five minutes, without an operator watching the price screen.
The price that sets your bill
Your bill is set by your commercial arrangement. For most plants this is a retail time-of-use rate plus a network demand charge for the highest peak. Only plants that have chosen spot exposure pay the wholesale spot price instead. The controller follows whichever structure sets your bill and turns it into a single price signal for each five minute interval. That signal tells the plant whether to use power now or hold off.
In practice most sites use the first two. The third only applies where you have appetite for spot exposure.
1 Retail time-of-use rate
Volumetric rate that varies by peak, shoulder and off-peak periods. This is the main signal for sites on a retail contract and the basis for Tariff Optimisation. Tariffs explained →
2 Maximum demand charge
Network charge set by your highest demand intervals each month. It sits on top of the time-of-use rate or the spot price and applies in every route. The controller avoids creating a new peak that would raise it. Maximum demand →
3 Wholesale spot price
Price set every five minutes by supply and demand in the NEM. Only relevant where the site has taken spot exposure under Route 03. NEM explained →
Most work uses the retail rate and demand charge (Routes 01 and 02). Tariff Optimisation is the default. Demand Response adds spot only where appetite exists.
The plant as a storage battery
Flexible load exists because treatment processes hold inventory that can be processed now or later within operating ranges, whichever assets your plant has. See WWTP Load Shifting for where that flexibility lives.
Rather than a fixed set point, the system adjusts set points continuously with price. Cheap periods lower the target tank level. Pumps draw down and process more while power is cheap. Expensive periods raise the target. The tank stores inflow. Response is smooth, not on or off, so the plant tilts toward cheap windows without breaching limits.
Looking ahead, not just reacting
Reacting to price now is not enough. Water takes time to move, a battery to charge, an engine to warm up. The algorithm positions the plant in advance using price, solar, weather, inflow and offtake forecasts.
An hour ahead
Holds ready for the next high-price interval and pre-empts storm inflows by drawing tanks down.
A day or more ahead
Positions reservoirs, sludge holdings and battery to ride out known peaks and make best use of forecast solar and price.
Every 5 minutes
Dispatches pumps and battery against the live price signal. Scheduled biosolids or recycled-water offtakes are part of the forecast. Levels are managed to meet the offtake without forcing upstream shutdowns.
Product offtakes included
A scheduled offtake is not an afterthought. The algorithm ensures the tank is at sufficient level to supply it without letting it climb so high that upstream processes are constrained.
Where the price is never allowed to win
The commercial objective is always subordinate to the process. Constraints are carried at every step:
- Reservoir and wet-well limits: hard low/high levels never breached, however extreme the price.
- Storm handling: large inflows predicted early, tanks drained to free capacity. Flood risk outranks price.
- Hydraulics and pump curves: real pipework and friction set achievable flow. The algorithm never asks for what the pipework cannot deliver.
- Pump wear: start/stop counts damped so pennies on electricity are not spent on switchgear and impellers.
- Maximum import cap: where the site caps grid draw, load is shed within safe limits.
- Operator override: full manual control retained at all times.
Every asset in one decision
Solar, battery, blowers and cogeneration join one coordinated decision against the same price signal.
- Solar offsets import whenever the sun shines.
- Battery charges when power is cheap or from solar surplus, discharges at high prices or when a demand-peak interval threatens.
- Blowers back off when electricity is expensive while holding dissolved oxygen the biology needs, making up the shortfall within the biological limit.
- Biogas generation runs when the price justifies it, banking gas when it does not, with waste heat coordinated back to the digester.
Every asset stays within its operating envelope. This same coordination underpins Tariff Optimisation (against time-of-use and demand) and Demand Response (against spot where relevant).
Designed by simulation, not guesswork
Tariff structures and historic energy data tell you what electricity costs and how the plant was actually operated. Neither shows what’s possible. Before running live, the site is built into a simulation validated against actual plant data and run over the period you advise of real prices, weather and flows, often a year and sometimes longer, giving a like-for-like comparison against real data rather than assumptions, not a single interval. The logic that runs live is the logic validated in simulation. See Energy Management and How We Work.
What this means for your site
No one needs to watch the market. Decisions are made automatically within limits the process sets, and the expected outcome, lower bill, fewer peaks, no lost effluent quality, is quantified in advance. See it on a full-year replay across four scenarios.