Experimental & legacy features
Warning
The methods on this page are not maintained and were not adapted to the refactored eDisGo code base. They may not work out of the box and are kept here for reference only. For the maintained flexibility and optimisation features, see Flexibility & optimisation.
Non-linear optimal power flow
An older multi-period non-linear OPF (perform_mp_opf) optimised generator
dispatch, curtailment and storage with regard to grid-expansion costs, using a
different formulation than the maintained PowerModels-based flexibility optimisation
(Multi-period optimal power flow). It is no longer maintained.
Curtailment heuristics
Two heuristics (in edisgo.flex_opt.curtailment) spatially distributed a given
curtailment target — obtained from an EHV/HV optimisation with
eTraGo — across the wind and solar generators
in the grid.
feedin-proportional (feedin_proportional) allocated curtailment in proportion
to each generator’s share of total feed-in:
where \(c_{g,t}\) is the curtailed power of generator \(g\), \(a_{g,t}\) its weather-dependent availability and \(c_{\text{target},t}\) the target.
voltage-based (voltage_based) allocated more curtailment to generators at
nodes with higher voltage-limit exceedance, solving a small linear program to set the
proportionality. See the git history for the full formulation.
Storage-positioning heuristic
A heuristic (edisgo.flex_opt.storage_positioning.one_storage_per_feeder) took a
given total storage capacity and distributed it over several smaller units to reduce
line overloading and voltage deviations, starting with the feeder with the highest
theoretical grid-expansion cost. Like the curtailment heuristics it was intended to
be used together with eTraGo, which optimised the storage capacity and operation.
For maintained storage handling see Battery storage.