Wp flex changed reinforcement

[birgits]

Description

This PR mainly changes the implementation of reduced_analysis. reduced_analysis can be used to conduct the grid reinforcement on a reduced number of time steps to avoid running the power flow for all time steps, including ones without grid issues, and thus speed up calculations. As it was implemented so far, the reduced_analysis could not be used to run the reinforcement for single LV grids or a subset of time steps. The latter is needed to use it in the catch_convergence_reinforce_grid function to conduct grid reinforcement for the converged time steps first.

The PR also now allows to weight time steps by estimated grid expansion costs analogous to how it was already possible in the selection of the most critical time intervals. This can be useful to further reduce the number of time steps to the most relevant ones.

Further, a fixes small bug in selection of time intervals.

Type of change

• [x] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

• [x] New and adjusted code is formatted using the pre-commit hooks
• New and adjusted code includes type hinting now
• [x] I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• [x] I have added tests that prove my fix is effective or that my feature works
• [x] New and existing unit tests pass locally with my changes
• [x] The Read the Docs documentation is compiling correctly
• [x] If new packages are needed, I added them the setup.py, and if needed the rtd_requirements.txt, the eDisGo_env.yml and the eDisGo_env_dev.yml.
• [x] I have added new features to the corresponding whatsnew file

[birgits]

Thank you so much @AnyaHe for your valuable comments. I implemented some of your suggestions and also have a few points I would like to discuss further. See comments above :)

[AnyaHe]

Thanks @birgits for addressing all the comments and the improvements in this PR. From my side, you can merge now. Great work! :)