Update eDisGo release.
- Update eDisGo version from 0.0.8 to 0.0.9
Add interactive map for documentation.
- Create and add interactive result map
- Add workshop jupyter notebook to docs
- Fix bug of period calculation
- removed duplicate matplotlib from setup.py
- fixed csv import
Making eGo quotable with zenodo.
- Registration at zenodo.org
This release contains documentation and bug fixes for the new features introduced in 0.3.0.
- Update of interactiv plot (iplot)
- Update of Documentation
- Update of eTraGo functionalities
- Update of eDisGo functionalities
- Change and update of API file scenario_setting.json
- Improved cluster plot of
- Improved cost differentiation
- Add jupyter notebook eGo tutorials
- Fix installation problems of the pypsa 0.11.0 fork (use pip 18.1)
- Fix parallel calculation of mv results
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.
- 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.iplotfor an interactive visualization
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 perform power flow simulations and optimizations for EHV, HV (eTraGo) and MV (eDisGo) grids.
Moreover, the use of the Dataprocessing versions
''v0.4.2'' is supported. Please note, that this release
is still under construction and only recommended for developers of
the open_eGo project.
Furthermore, overall cost aggregation functions are available.
- Cleaned and restructured eGo classes and functions
- Move classes of eGo from results.py to io.py
- Move serveral function
- Introduce new files for eDisGo handling
- Introduce new file storages.py for eTraGo
- Updated eTraGo 0.6 and integrated eTraGo’s new functions and features to eGo
- Updated eDisGo 0.0.3 version which includes the features of a parallelization for custom function and other important API changes.
- Started to implemented pep8 style to eGo Code
- Implemented logging function for the whole model
- Using the Restfull-API for the OpenEnergy Database connection, buy using ego.io v0.4.2. A registration is needed and can be done on openenergy-platform.org/login
- Remove functionalities from
ego_main.pyto the eGo class
- Fixed eTraGo scenario import of
- As an external user you need to have an account on the openenergy-platform.org/login
- In future versions, all MV grids (ding0 grids) will be queried from your database. However, in this version all MV grids have to be generated with the tool ding0 and stored in eGo’s data folder.
- Total operational costs are missing in this release
As this is the second release of eGo. This Release introduce the results class and is still under construction and not ready for a normal use.
- 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
- The ‘direct_specs’ function is not working and needs to be set to
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.
- Interface between eTraGo and eDisGo
- Plots with folium
- First result structure