Release 0.9.0

Added features

• eTraGo is now compatible with Python 3.8
• eTraGo can now import and optimize networks that include other energy sectors such as gas, heating and mobility
• Various flexibility options from different energy sectors can be considered in the optimization:
  Weather dependent capacity of transmission lines (Dynamic Line Rating), Demand Side Management, Flexible charging of electric vehicles, Heat and hydrogen stores, Power2Hydrogen, Hydrogen2Power, Methanation and Steam Methane Reforming
• eTraGo arguments can now be partially provided and updated
• eTraGo can now import datamodels from databases without using the ego.io
• Existing clustering methods were adapted to be able to reduce the complexity of not electrical sectors
• Improvement of the ehv clustering (much faster now)
• A new clustering method named "k-medoids Dijkstra Clustering" (can be called by "kmedoids-dijkstra") was implemented. This method considers the electrical distance between the buses in the network. It is also available for the methane grid.
• It is possible to select if foreign buses are considered or not during the clustering process.
• The number of CPUs used to perform the clustering can be provided by the user.
• Some more options are available to conduct a reduction in temporal dimension: segmentation, clustering to typical weeks and months
• A temporal disaggregation is available through a 2-level-approach including a dispatch optimization on the temporally full complex model. To limit the RAM usage, you can optionally divide the optimisation problem into a chosen number of slices.
• New plotting functions to visualize the optimization results from all the included energy sectors were implemented
• Functions to analyze results were updated to consider new sectors