mosaik ecosystem

Mosaik as a co-simulation tool organizes the data exchange between simulators and coordinates the execution of the connected simulaters. This part is called mosaik mosaik-core and contains mosaik itself and APIs for multiple programming languages.

mosaik is a co-simulation library. The components and tools form the mosaik ecosystem.

Mosaik is a co-simulation library. The components and tools form the mosaik ecosystem.

Mosaik-core without any connected simulators doesn’t do much. This is why we provide some simple and free simulators so that it is possible to start with a working Smart-Grid simulation. These simulators belong to a part of mosaik’s ecosystem called mosaik mosaik-components.

To see how these components can be coupled to simulations, also some example scenarios are provided in mosaik mosaik-examples.

Mosaik is developed following the “lean and mean” principle. That means that we try to keep the software as simple as possible in order to keep it efficient and easy to maintain. In order to make it easier to set up and run experiments with mosaik we provide some tools that help building scenarios, connecting simulators or to visualize and analyze the simulation results. These tools are located in the mosaik mosaik-tools-library.

There are also some implementations done by external users of mosaik. We give an overview of the mosaik external components and mosaik external scenarios we know here.

mosaik mosaik-core

The root folder contains mosaik itself and the high-level API implementations are provided in the API folder.

mosaik mosaik-components

mosaik mosaik-examples

mosaik mosaik-tools

mosaik basic simulators

In order to test custom-made simulators, two basic simulators are provided to use and connect to.

  • The InputSimulatoris a simulator that can be used to feed either a constant value or the value of a function into a designated simulator ready to handle the data.

  • The OutputSimulator writes data from a custom simulator into a python dictionary. Users can access this dictionary by calling get_dict()on a created output simulator entity.

Below is an example code snippet that connects the input simulator with the output simulator and executes ten time steps. After the simulation is done, the dictionary including the values received by the input simulator is printed.

# The output simulator is initialized.
output_dict = world.start("OutputSim")

# Two entities of the output simulator model are created.
output_model = output_dict.Dict.create(2)

# The input simulator is initialized.
input = world.start("InputSim", step_size=1)

# One function input simulator entity is created.
input_model_func = input.Function.create(1, function=sample_function)

# One constant input simulator entity is created.
input_model_const = input.Constant.create(1, constant=2)

# The input entities are connected to separate output entities
world.connect(input_model_func[0], output_model[1], "value")
world.connect(input_model_const[0], output_model[0], "value")

# Run simulation.

# Dictionary content is printed.

mosaik external components

These components are developed by external users of mosaik and we can not guarantee or support the flawless integration of these tools with mosaik. If you also have implemented additional tools for mosaik, simulation models or adapters, feel free to contact us at mosaik [ A T ] to be listed here.

  • pysimmods contains some simulation models, which can be used in mosaik scenarios.

  • MIDAS contains a semi-automatic scenario configuration tool.

  • mosaik-docker is a package for the deployment of mosaik with Docker.

  • ZDIN-ZLE components contains the research and development of digitalized energy systems in ZLE using mosaik (collection of simulation models).

  • nestli (Neighborhood Energy System Testing towards Large-scale Integration) is a co-simulation environment for benchmarking the performance of BACS (building automation and control systems). Is uses EnergyPlus and FMUs with mosaik.

  • toolbox_doe_sa is a toolbox with Design of Experiment (DoE) and Sensitivity Analysis (SA) methods developed in the ERIGrid 2.0 project.

  • mosaik-demod is a domestic energy demand modeling simulator.

  • palestrai-mosaik is an adapter to integrate palaestrAI (an universal framework for multi-agent artificial intelligence) into mosaik.

mosaik external scenarios

These scenarios are developed by external users of mosaik and we can not guarantee or support the flawless practicability.