Skip to content

Releases: openego/eGo

Release 0.3.4

10 Dec 10:23
Compare
Choose a tag to compare

Update of eDisGo version.

Release 0.3.3

07 Dec 12:39
Compare
Choose a tag to compare

Fixing and Documentation Release

Release 0.3.2

27 Oct 16:26
Compare
Choose a tag to compare

Making eGo quotable with zenodo.

Release 0.3.1

27 Oct 11:03
3436d73
Compare
Choose a tag to compare

This release contains documentation and bug fixes for the new features introduced in 0.3.0.

Find more information on openego.readthedocs.io

Release 0.3.0

07 Sep 18:55
Compare
Choose a tag to compare

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.

Read more on here

Birthday Release 0.2.0

19 Jul 16:26
ec16791
Compare
Choose a tag to compare

Fundamental structural changes of the eGo tool are included in this release. A new feature is the integration of the MV grid power flow simulations, performed by the tool eDisGo.. Thereby, eGo can be used to perforem power flow simulations and optimizations for EHV, HV (eTraGo) and MV (eDisGo) grids.

...

Read more on: openego.readthedocs.io

Result class implementation

29 Mar 14:34
03378ba
Compare
Choose a tag to compare

This is the second release of eGo. The Release introduce the result class and is still under construction and not ready for a normal use.

Added features

  • Update of Interface between eTraGo and eDisGo (specs)
  • New structure of eGo module / resulte class
  • Restructuring of functions
  • Add import function of eTraGo results form oedb

First release of eGo

02 Feb 12:30
Compare
Choose a tag to compare
First release of eGo Pre-release
Pre-release

As this is the first release of eGo. The tool eGo use the Python3 Packages eTraGo (Optimization of flexibility options for transmission grids based on PyPSA) and eDisGo (Optimization of flexibility options and grid expansion for distribution grids based on PyPSA) for an electrical power calculation from extra high voltage to selected low voltage level.