What is optimisation?

Optimisation's machine learning algorithm

Optimisation is a machine learning algorithm that makes decisions on behalf of your customers on the best way to manage their devices.

The algorithm uses three sets of data to make these decisions:

Forecasts: Predictions on how much energy the home will use and how much the PV panels will produce. The algorithm uses past data and weather data to make these forecasts.

Tariffs: How much the home pays to buy and sell energy for each half-hour period of the day.

Hardware specifications: What their solar panels and batteries are doing, how charged they are and their maximum charge rates.

Optimisation modes explained

The algorithm then uses this data to make decisions on what mode to put the battery in, the decisions are made every 5 minutes.

• Charge from Solar

  • Battery charges only from Solar; this mode may also be seen overnight, as it prevents the battery from discharging to the grid or home. Ensuring the battery is full for when it's needed most.

• Charge from Grid and Solar

  • Battery continues charging from solar while also pulling power from the grid.

• Discharge for Usage

  • Allows the battery to discharge into the home for general usage.

• Discharge for Usage and Grid

  • Continues to allow home usage from the battery while also discharging to the grid, earning you money from your export tariff.

• Balance Solar and Usage

  • The battery charges up if the home is producing more PV energy than it's using, and discharges if the home is using more than it's producing, aiming to keep the system as self-sufficient as possible. This is the standard setting for home batteries.

     

These modes are displayed to consumers in the app under Optimisation history on the home page.

Optimisation history explained: