Edge
SWIFT-BOX
Capture and historise right at the machine.
Learn more →Case study · battery storage
A battery controlled
from load profile, weather and market
An industrial storage system of 17 MWh alongside a PV array of 3 MWp peak. The control logic is not driven by rules of thumb but by three data sources that line up cleanly: load profile, weather forecast and exchange prices.
Discuss a similar project
01
Challenge: three sources, one control system
An industrial site operates a battery storage system of 17 MWh alongside a PV array of 3 MWp peak. The operating mode of the storage system should not be manually controlled but automatically decided from three sources: the measured load profile of the site, the weather forecast for PV feed-in, and current exchange electricity prices.
The technical challenge is not the control logic itself but the fact that these three sources have different formats, time resolutions and latencies. Load profile data arrives in real time from meters, weather data in hourly forecast intervals from an API, and exchange data in 15-minute resolution. If these sources are not cleanly aligned in time, the control logic runs on inconsistent inputs.
We contributed on the data side: time-series capture, normalisation of time resolutions and a data pipeline that merges the three sources so that the control logic runs on reliable and temporally consistent values.
17 MWhindustrial battery
3 MWpPV peak output
3data sources: load, weather, market
EWEgrid operator for the generating plant
Questions about this project
Which technologies were used for the data pipeline?
Time-series database for load profile data, REST API integration for exchange and weather data, Node-RED for orchestrating the pipeline and normalising time resolutions. The data is held in a shared timestamp model that consistently feeds the control logic.
Is a similar project possible for smaller storage systems?
Yes. The principle of data-driven storage control is scalable. Even for storage systems of a few hundred kWh it is worth integrating load profile and PV forecast when energy costs represent a significant share of operating costs. The automation audit provides a first assessment of when the effort pays off.
What was Iniationware's role in this project?
We took on the data part: time-series capture, normalisation and pipeline. The control logic itself, the decision of when the storage charges or discharges, was developed by the client and their energy manager. The clean data foundation was the prerequisite for that logic to work reliably.
Storage control on a reliable data foundation.
We bring load profile, weather forecast and exchange data into a consistent pipeline on which your control logic runs.
Discuss a projectRelated services for this project
Data
iniationOS
One shared data layer for ERP, MES and quality.
Learn more →OPC UA
OPC UA integration
Connect machines and build information models.
Learn more →Interested, but not ready to enquire?
An e-mail address is enough. We come back once with a short read on it, no newsletter.