Represent typical days while maintaining storage for the entire year

[Vincenzo Romano]

Dear PyPSA community,

I’m building a model with integer/binary variables that becomes intractable over a full year. I need hourly resolution but also a full-year horizon for storage to capture seasonal effects. A common workaround is to cluster time into N typical days and solve on N×24 snapshots for all variables except storage, which remains on 8760 snapshots.

Does PyPSA support this mixed time discretisation, or is there a recommended workaround?

Thank you.

Kind regards, 

Vincenzo