AI control for Home Battery

Objective
The stock market price-optimized battery control enables households to obtain the cheapest and cleanest electricity by making intelligent decisions about charging and discharging processes of a battery. The algorithm combines AI-based forecasts and dynamic adjustments to current stock exchange current prices to efficiently control electricity consumption, storage and feed.
Functionality
  1. Consumption and generation forecast: With the help of artificial intelligence, a precise forecast of electricity consumption and electricity generation of the household is created for the coming hours. This takes into account factors such as:
    • Historical consumption data
    • Weather forecasts for photovoltaic generation
    • Habits of the household
  2. Timetable calculation: Based on the forecasts and the current stock exchange current prices (spot market) including all allowances, dynamic timetables are calculated every 5 minutes. Take this into account:
    • The current state of charge (State of Charge, SoC) and the capacity of the Home Battery
    • Stock -up power prices that are obtained directly from the stock exchange
    • Minor remuneration
    • Storage losses and potential profits
  3. Dynamic decision -making logic: The algorithm decides in real time which of the following strategies is the optimal:
a) Pause of the discharge process:
  • If the electricity cover from the network is cheaper than the own consumption of the battery, the discharge process is paused. This protects the battery and preserves its capacity for hours in which the electricity cover is more expensive.
b) Battery load from the network for forecast network cover:
  • If the current stock exchange current price is lower than the forecast network cover costs in more expensive hours, the battery will be loaded in a targeted manner.
  • Storage losses and potential profits are taken into account to ensure that the loading process remains economical.
c) Battery load from the network at very affordable electricity prices:
  • If the current stock market price including all allowances is lower than the feed -in tariff, the battery is loaded from the network. This increases the profit.
  • Here, too, memory losses are taken into account to ensure maximum efficiency.
d) Self -consumption optimization:
  • If neither the breakdown of the discharge nor charging from the network is economically advantageous, the battery is used as usual to maximize your own consumption.