Use pypsa's optimize_with_rolling_horizon() functionality

[ulfmueller]

in particular for our market simulation... see pypsa depends on #663

[ulfmueller]

First running example is implemented here. But details remain to be done:

• [ ] define a suitable planning horizon and overlap primarily with a purpose of realistic assumption (and not with a purpose of reducing computational burden). Try to get NEP insights and/or do more literature research, consult market experts.
• [ ] move central parameters if useful to the appl args

[ClaraBuettner]

When I understand the code correctly, there is currently no extra_functionality set in the rolling_horizont optimization. We would need that at least for defining the CHP heat and electricity dispatch. We should find out if it is possible to add extra_functionalities to the rolling_horizont optimization and if yes, we need to use the constraints for linopy. They are already translated, but these changes are not on dev yet.

[ClaraBuettner]

When I understand the code correctly, there is currently no extra_functionality set in the rolling_horizont optimization. We would need that at least for defining the CHP heat and electricity dispatch. We should find out if it is possible to add extra_functionalities to the rolling_horizont optimization and if yes, we need to use the constraints for linopy. They are already translated, but these changes are not on dev yet.

Update: We can add extra_functionalities to the rolling_horizont optimization easily. So we just need the translated constraints from the other branch. I will do this soon.

[ClaraBuettner]

The comments listed above are already included in eTraGo. There might be some updates in the future, but I think it is better to open a new issue by then. So I will close this issue now.