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. PyPSA is designed to scale well with large networks and long time series.
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 is in sphinx reStructuredText format in doc/.
PyPSA can calculate:
- static power flow (using both the full non-linear network equations and the linearised network equations)
- linear optimal power flow (optimisation of power plant and storage dispatch within network constraints, using the linear network equations, over several snapshots)
- security-constrained linear optimal power flow
- total electricity system investment optimisation (using linear network equations, over several snapshots simultaneously for optimisation of generation and storage dispatch and investment in 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
- simple hydroelectricity with inflow and spillage
Functionality that will definitely be added soon (see also doc/todo.rst):
- Graphical plotting of networks with power flow
- Integration of heating and gas sectors (CHPs, heat pumps, P2H, P2G, etc.)
- 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
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:
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.
PyPSA has a Google Group forum / mailing list.
PyPSA is released as free software under the GPLv3, see LICENSE.txt.