Release v0.3.0 (September 07, 2018)
+++++++++++++++++++++++++++++++++++

Power Flow and Clustering. eGo is now using eTraGo non-linear power flows based 
on optimization results and its disaggregation of clustered results 
to an original spatial complexities. With the release of eDisGo speed-up options, 
a new storage integration methodology and more are now available.  


Added features
--------------

* Update of dependencies
* Implementing of Ding0 grid parallelization
* Redesign of scenario settings and API simplifications
* Adding and using the Power Flow of eTraGo in eGo
* Testing  and using new dataprocessing Version v0.4.3, v0.4.4 and v0.4.5  
* make eGo installable from pip via ``pip3 install eGo -- process-dependency-links``
* Implementing eDisGo's storage distribution for MV and LV grids
* Improved logging and the creation of status files
* Maximal calculation time for ding0 grids can be set by user
* eDisGo results import and export (all eGo-relevant data from eDisGo can be re-imported after a run)
* Storage-related investment costs are also allocated to MV grids
* Update of cluster plots
* Plot of investment costs per line and bus
* Update of ``ego.iplot`` for an interactive visualization 
  


