mosaik 2.0

Mosaik

Mosaik is a simulation compositor for Smart Grid simulations.

It lets you re-use existing simulators and couple them to simulate large-scale Smart Grid scenarios. Mosaik offers powerful mechanisms to specify and compose these scenarios.

>>> import mosaik
>>>
>>> sim_config = {
...     'ExampleSim': {'python': 'example_sim.mosaik:ExampleSim'},
... }
>>>
>>> def create_scenario(world):
...     exsim1 = world.start('ExampleSim')
...     exsim2 = world.start('ExampleSim')
...
...     a = [exsim1.A(init_val=0) for i in range(3)]
...     b = exsim2.B.create(2, init_val=0)
...
...     for i, j in zip(a, b):
...         world.connect(i, j, ('val_out', 'val_in'))
>>>
>>> world = mosaik.World(sim_config)
>>> create_scenario(world)
>>> world.run(until=2)
Progress: 25.00%
Progress: 50.00%
Progress: 75.00%
Progress: 100.00%

$ pip install mosaik

Changelog

2.0 – 2014-09-22

• Mosaik 2 is a complete rewrite of mosaik 1 in order to improve its maintainability and flexibility.

• Removed features:

  • The mosl DSL (including Eclipse xtext and Java) are now gone. Mosaik now only uses Python.

  • Mosaik now longer has executables but is now used as a library.

  • The platform manager is gone.

  • The database is now a separate package, see mosaik-hdf5.

  • The old web UI is gone.

• Mosaik now consists of four core components with the following feature sets:

  • mosaik Sim API

    • The API has bean cleaned up and simplified.

    • Simulators and control strategies share the same API.

    • There are only four calls from mosaik to a simulator: init, create, step and get_data.

    • Simulators / processes can make asynchronous requests to mosaik during a step: get_progress, get_related_entities, get_data, set_data.

    • ZeroMQ with JSON is replaced by plain network sockets with JSON.

  • Scenarios:

    • Pure Python is now used to describe scenarios. This offers you more flexibility to create complex scenarios.

    • Scenario creation simplified: Start a simulator to get a model factory. Use the factory to create model instances (entities). Connect entities. Run simulation.

    • Connection rules are are no based on a primitive connect function that only connects two entities with each other. On top of that, any connection strategy can be implemented.

  • Simulation Manager:

    • Simulators written in Python 3 can be executed in process.

    • Simulators can be started as external processes.

    • Mosaik can connect to an already running instance of a simulator. This can be used as a replacement for the now gone platform manager.

  • Simulation execution:

    • The simulation is now event-based. No schedule and no synchronization points need to be computed.

    • Simulators can have different and varying step sizes.

• Mosaik ecosystem:

  • A high-level implementation of the mosaik 2 API currently exists for Python and Java.

  • mosaik-web is a simple visualization for mosaik simulations. See https://bitbucket.org/mosaik/mosaik-web.

  • mosaik-pypower is an adapter for the PYPOWER load flow analysis library. See https://bitbucket.org/mosaik/mosaik-pypower and https://github.com/rwl/PYPOWER.

  • mosaik-csv and mosaik-householdsim are simple demo simulators that you can use to “simulate” CSV data sets and load-profile based households. See https://bitbucket.org/mosaik/mosaik-csv and https://bitbucket.org/mosaik/mosaik-householdsim.

  • There is a repository containing a simple demo scenario for mosaik. See https://bitbucket.org/mosaik/mosaik-demo.

You can find information about older versions on the history page

Authors

The original concepts for mosaik were developed by Steffen Schütten and Stefan Scherfke.

The author of mosaik version 2 is Stefan Scherfke.