pypsa 0.3.2

Python for Power Systems Analysis

Python for Power Systems Analysis

PyPSA stands for “Python for Power System Analysis”. It is pronounced “pipes-ah”.

PyPSA is a free software toolbox for simulating and optimising modern electric power systems that include features such as variable wind and solar generation, storage units and mixed alternating and direct current networks.

As of 2016 PyPSA is under heavy development and therefore it is recommended to use caution when using it in a production environment. Some APIs may change - those liable to be updated are listed in the doc/todo.rst.

PyPSA was initially developed by the Renewable Energy Group at FIAS to carry out simulations for the CoNDyNet project, financed by the German Federal Ministry for Education and Research (BMBF) as part of the Stromnetze Research Initiative.

Documentation

Documentation can be found in sphinx reStructuredText format in doc/ and as a website and as a pdf.

What PyPSA does and does not do (yet)

PyPSA can calculate:

• static power flow (using both the full non-linear network equations and the linearised network equations)

• optimal power flow (optimisation of power plant dispatch within network constraints, using the linear network equations)

• total electricity system optimisation (using linear network equations, over several snapshots simultaneously for optimisation of generation and storage dispatch and the capacities of generation, storage and transmission)

It has models for:

• meshed multiply-connected AC and DC networks, with controllable converters between AC and DC networks

• conventional dispatchable generators

• generators with time-varying power availability, such as wind and solar generators

• storage units with efficiency losses

• hydroelectricity with inflow and spillage

Functionality that will definitely by added soon (see also doc/todo.rst):

• Graphical plotting of networks with power flow

• Integration of heating sector (CHPs, heat pumps, etc.)

• Security Constrained Linear OPF

• Simple RMS simulations with the swing equation

• Distributed active power slack

• Non-linear power flow solution using analytic continuation in the complex plane

Functionality that may be added in the future:

• Unit Commitment using MILP

• Short-circuit current calculations

• Dynamic RMS simulations

• Small signal stability analysis

• Interactive web-based GUI

• OPF with the full non-linear network equations

• Dynamic EMT simulations

• Unbalanced load flow

• Port to Julia

Screenshots and example Jupyter/iPython notebooks

There are extensive examples available as Jupyter/iPython notebooks. They are also described in the doc/examples.rst and are available as Python scripts in examples/.

Some screenshots:

What PyPSA uses under the hood

PyPSA is written and tested to be compatible with both Python 2.7 and Python 3.4.

It leans heavily on the following Python packages:

• pandas for storing data about components and time series

• numpy and scipy for calculations, such as linear algebra and sparse matrix calculations

• pyomo for preparing optimisation problems (currently only linear)

• networkx for some network calculations (such as discovering connected networks)

• py.test for unit testing

The optimisation uses pyomo so that it is independent of the preferred solver (you can use e.g. the free software GLPK or the commercial software Gurobi).

The time-expensive calculations, such as solving sparse linear equations, are carried out using the scipy.sparse libraries.

Licence

PyPSA is released as free software under the GPLv3, see LICENSE.txt.