Comparable Software#

The PyPSA paper contains a discussion of PyPSA’s features compared to other software tools and a functionality comparison in Table III.

Free software#

  • PYPOWER - a Python, numpy, scipy port of MATPOWER, compared to PyPSA below

  • pandapower - a Python based extension of PYPOWER that uses pandas “to create an easy to use network calculation program aimed at automation of power system analysis and optimization in distribution and sub-transmission networks”

  • GridCal - a Python-based extension of PYPOWER that includes time series and load flow methods using analytic continuation

  • MATPOWER - a Matlab-based tool for static power system computations

  • PSAT - a general Matlab-based tool for (most) power system calculations

  • Open Energy Modelling Framework - Python and Pyomo based framework for optimisation which includes all energy sectors in a general framework

  • Calliope - Python and Pyomo based framework for energy system optimisation

  • OSeMOSYS - systems optimization model for long-run energy planning

  • urbs

  • minpower

  • DiSC

  • IEEE OSS list


  • PowerGAMA

  • NEMO

  • Mosaik-PYPOWER

  • OpenDSS

  • MatDyn

  • GridLAB-D

  • CIMpy

  • vSPD - Vectorised Scheduling, Pricing and Dispatch (vSPD) - an audited, mathematical replica of SPD, the pricing and dispatch engine used in the New Zealand electricity market.

Non-free software#

Comparison with selected packages#

PyPSA is compared to PYPOWER in the following table:



Object-oriented, data stored in pandas DataFrames

Numpy integer-indexed arrays

Non-linear power flow

Non-linear power flow

Only linear OPF

Non-linear and linear OPF

Optimisation over multiple time points

Single time-point optimisation

Generators, storage models, hydro, sector coupling

Just generators

Mixed AC-DC modelling

Just AC, single synchronous area

Conceived in Python

Port of Matlab-based MATPOWER