Home battery management system using deep learning

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Hello! I’m a senior software engineering student and I’m new to this community.
I just want to ask about the possiblity, and if yes, the fastest way to use openems to have a program that uses the output of (PV generation forecasting) and (home consumption forecasting) to make optimized decisions about the day-ahead scheduling of battery storage system (i.e., the ouptut of the program will be a schedule of “when” and “by how much amount of electricty” the batteries will be “charged” or “discharged”) ?

I really need this for my final year project.

Thank you in advance!

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Hi @mounir,

I am working on similar topics for our FENECON product “FEMS App Dynamischer Stromtarif” / “FEMS App Time-of-Use Tariff”.

See this link for technical details: FEMS App Dynamischer Stromtarif

The code is under heavy development and improvement, but it’s production ready and in use by hundreds of productive systems. It should be a solid basis for your project.

Regards,
Stefan