Python for Power System Analysis (PyPSA) Version 0.12.0

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern power systems that include features such as conventional generators with unit commitment, variable wind and solar generation, storage units, sector coupling and mixed alternating and direct current networks. PyPSA is designed to scale well with large networks and long time series. Find out more at:

https://pypsa.org/

and

http://github.com/FRESNA/PyPSA

This is release 0.12.0 of PyPSA.

Hyperlinked release notes can be found here: https://pypsa.org/doc/release_notes.html#pypsa-0-12-0-30th-november-2017

This release contains new features and bug fixes.

* Support for Pyomo’s persistent solver interface, so if you’re making small changes to an optimisation model (e.g. tweaking a parameter), you don’t have to rebuild the model every time. To enable this, network_lopf has been internally split into build_model, prepare_solver and solve to allow more fine-grained control of the solving steps. Currently the new Pyomo PersistentSolver interface is not in the main Pyomo branch, see the pull request; you can obtain it with pip install git+https://github.com/Pyomo/pyomo@persistent_interfaces

* Lines and transformers (i.e. passive branches) have a new attribute s_max_pu to restrict the flow in the OPF, just like p_max_pu for generators and links. It works by restricting the absolute value of the flow per unit of the nominal rating abs(flow) <= s_max_pu*s_nom. For lines this can represent an n-1 contingency factor or it can be time-varying to represent weather-dependent dynamic line rating.

* The marginal_cost attribute of generators, storage units, stores and links can now be time dependent.

* When initialising the Network object, i.e. network = pypsa.Network(), the first keyword argument is now import_name instead of csv_folder_name. With import_name PyPSA recognises whether it is a CSV folder or an HDF5 file based on the file name ending and deals with it appropriately. Example usage: nw1 = pypsa.Network("my_store.h5") and nw2 = pypsa.Network("/my/folder"). The keyword argument csv_folder_name is still there but is deprecated.

* The value network.objective is now read from the Pyomo results attribute Upper Bound instead of Lower Bound. This is because for MILP problems under certain circumstances CPLEX records the Lower bound as the relaxed value. Upper bound is correctly recorded as the integer objective value.

* Bug fix due to changes in pandas 0.21.0: A bug affecting various places in the code, including causing network.lopf to fail with GLPK, is fixed. This is because in pandas 0.21.0 the sum of an empty Series/DataFrame returns NaN, whereas before it returned zero. This is a subtle bug; we hope we’ve fixed all instances of it, but get in touch if you notice NaNs creeping in where they shouldn’t be. All our tests run fine.

* Bug fix due to changes in scipy 1.0.0: For the new version of scipy, csgraph has to be imported explicit.

* Bug fix: A bug whereby logging level was not always correctly being seen by the OPF results printout is fixed.

* Bug fix: The storage unit spillage had a bug in the LOPF, whereby it was not respecting network.snapshot_weightings properly.

We thank René Garcia Rosas, João Gorenstein Dedecca, Marko Kolenc, Matteo De Felice and Florian Kühnlenz for promptly notifying us about issues.