Installation#

Getting Python#

If it is your first time with Python, we recommend conda, mamba or pip as easy-to-use package managers. They are available for Windows, Mac OS X and GNU/Linux.

It is always helpful to use dedicated conda/mamba environments or virtual environments.

Getting a solver for optimisation#

PyPSA passes optimisation problems for Power System Optimization to an external solver. PyPSA is known to work via linopy with the free software

and the non-free software, commercial software (for some of which free academic licenses are available)

For installation instructions of these solvers for your operating system, follow the links above.

Depending on your operating system, you can also install some of the open-source solvers in a conda or pip environment.

For HiGHS on all operating systems:

pip install highspy

For GLPK on all operating systems:

conda install -c conda-forge glpk

For CBC on all operating systems except for Windows:

conda install -c conda-forge coincbc

Note

Commercial solvers such as Gurobi, CPLEX, and Xpress currently significantly outperform open-source solvers for large-scale problems. It might be the case that you can only retrieve solutions by using a commercial solver.

Installing PyPSA with conda#

If you are using conda you can install PyPSA with:

conda install -c conda-forge pypsa

In all of the above commands you can replace conda with mamba if you use this alternative.

Installing PyPSA with pip#

If you have the Python package installer pip then just run:

pip install pypsa

If you’re feeling adventurous, you can also install the latest master branch from github with:

pip install git+https://github.com/PyPSA/PyPSA.git

Conservative installation#

If you’re very conservative and don’t like package managers, you can just download the code from the PyPSA github repository and add the directory of PyPSA to your python path with e.g.:

import sys

sys.path.append("path/to/PyPSA")

import pypsa

Upgrading PyPSA#

We recommend always keeping your PyPSA installation up-to-date, since bugs get fixed and new features are added. PyPSA is also only tested with the latest stable versions of all the dependent packages for the respective Python versions.

To upgrade PyPSA with pip, do at the command line:

pip install -U pypsa

To upgrade PyPSA with conda, do at the command line:

conda update pypsa

Don’t forget to read the Release Notes regarding API changes that might require you to update your code.