Optimise power purchasing and battery storage on the market
Energy traders optimise purchasing and battery storage on the electricity market
Fits: Finance & accounting · Purchasing · Production, engineering & maintenance
The battery charges when electricity is cheap and discharges when it is expensive. Purchase volumes fit load and price forecasts better, and expensive balancing energy is needed less often.
Is this for you?
- You operate a battery storage system or are planning one, and you trade on the day-ahead or intraday market.
- Load profiles, generation forecasts and price data are available digitally at 15-minute or hourly resolution.
- There is a trading team with clear limits and a risk function that approves limits.
Download the day-ahead prices for two past days from a public source or take a test series, and use the template below to have a charging and discharging schedule calculated for a hypothetical battery. Recalculate two hours yourself. This shows whether the logic with efficiency and state of charge is right before you discuss a system.
How to go about it
- Set the revenue goal, trading limits and storage limits
- Connect exchange prices, forecasts and storage data
- Set up schedule and bidding rules
- Have schedules suggested in parallel first
- Submit bids automatically in stages
- Evaluate revenue, balancing energy and battery condition
Templates to copy
The complete guide
- 6 steps explaining exactly what to do
- 3 proven templates to copy into your own AI
- Safe use: data, checking, deciding, informing
- Pitfalls, effort and how to recognise success
With the training you get all 430 guides for as long as your access runs.
Same approach, other use cases
6 more use cases follow the pattern “Managing prices & offers”.
EV-04 · Legal status 08.10.2026