Motivation / Problem
Grid reinforcement is currently very simplified and can produce unreasonable results — e.g. a large
number of parallel lines — because only a limited set of measures exists and there is no logic for
choosing the appropriate measure per situation.
This issue is part of #15.
Proposed solution
Affected files
edisgo/flex_opt/reinforce_grid.py
edisgo/flex_opt/reinforce_measures.py
edisgo/edisgo.py (EDisGo.reinforce() entry point / parameters)
Acceptance criteria
- At least grid separation and switch balancing are implemented and selectable
- A documented selection logic picks the method based on the constraint type and avoids unreasonable parallel-line results
- Tests cover each new method
- New methods and selection logic are documented
References / related
Motivation / Problem
Grid reinforcement is currently very simplified and can produce unreasonable results — e.g. a large
number of parallel lines — because only a limited set of measures exists and there is no logic for
choosing the appropriate measure per situation.
This issue is part of #15.
Proposed solution
Affected files
edisgo/flex_opt/reinforce_grid.pyedisgo/flex_opt/reinforce_measures.pyedisgo/edisgo.py(EDisGo.reinforce()entry point / parameters)Acceptance criteria
References / related