mosaik-pandapower-2 0.3.3

An adapter to connect mosaik to pandapower

mosaik-pandapower-2

This is an adapter for using the network calculation program pandapower in a mosaik simulation.

This simulator is still work in progress. In particular, not every desirable attribute is implemented yet. If you have need for a particular entity or attribute, leave an issue here.

Usage

Installation

This package can be installed from PyPI as mosaik-pandapower-2.

This simulator supports simbench grids. If you want to use them, you need to install the simbench package from PyPI.

pandapower can be sped up by also installing numba. As this can be tricky on some systems (and not strictly necessary), it is not listed as an explicit dependency.

Setup

First, add the simulator to your SIM_CONFIG as normal:

SIM_CONFIG = {
    "Pandapower": {"python": "mosaik_components.pandapower:Simulator"},
    ...
}

Having created your world, you can then start an instance of the simulator via

pp_sim = world.start("Pandapower", step_size=900)

The step_size specifies at which steps this simulator runs. (The default is step_size=900.) If you set step_size to None, the simulator will run in event-based mode, i.e. it will step whenever it receives new input.

Finally, you can create the Grid entity. There are several ways of doing this:

• If you have a pandapowerNet instance net in your scenario and the pandapower simulator is running in the same Python instance, you can use that grid by calling

  grid = pp_sim.Grid(net=net)
  

  Note that the intended use for this is that you set up the grid using pandapower's functions and then pass the pandapowerNet to the adapter. The adapter does not expect the supplied net to be changed by anything (but itself) afterwards. If you continue to tinker with the grid, your results may be incorrect.

• If the grid is in a JSON file (in pandapower’s format), you can call

  grid = pp_sim.Grid(json=path_to_json)
  

• Similarly, if the grid is in an Excel file,

  grid = pp_sim.Grid(xlsx=path_to_xlsx)
  

• If you want to use one of the network creation functions in pandapower.networks, you can specify

  grid = pp_sim.Grid(network_function=function_name, params=params)
  

  where function_name is the name of the function as a string and params is a dictionary that will be used as the keyword arguments to that function (it will default to {} if not given).

• Finally, if you want to use a simbench grid,

  grid = pp_sim.Grid(simbench=simbench_id)
  

  This method requires simbench to be installed in the same (virtual) environment as the adapter. This does not happen automatically when installing mosaik-pandapower-2, as we don't want to burden users who don't need it with this dependency.

In every case, you will get a Grid entity grid. The simulator supports only one such entity. In case that you want to simulate several grids, you need to start several instances of the simulator. (Design note: Requiring multiple grids should be rare; restricting to one of them shortens the entity IDs of the children as we don’t need to track to which grid they belong.)

Identifying grid elements

The Grid entity grid will have a child entity for each supported element present in the grid. You can access them via grid.children. You can filter for specific types of entities by checking the child entity's type attribute.

The entity IDs of the children follow the format ElementType-Index where ElementType is the same as the type and Index is the element's index in the element's table in the pandapowerNet object.

If you are using mosaik 3.3 or later, each entity will also have an extra_info field holding a dict with additional information about this entity. This will always include the entity's index (so you don't need to parse its entity ID) and its name in the pandapower grid. Depending on the element, other information is included as well. If you are missing a field, feel free to leave an issue.

Earlier versions of mosaik do not support extra_info in this way. To still enable you to access it, the simulator has a get_extra_info extra method, which can be called like so, after creating the grid:

extra_info = pp_sim.get_extra_info()

This is a dict mapping each entity ID to its entity's extra info.

Connecting other simulators to the grid

The most common case when connecting entities to the grid is to connect them as loads or static generators. (Essentially, this encompasses all entities that provide real and reactive power values.) Therefore, this simulator is optimized for this case and you can connect these entities directly to the Bus entities. Use the P_gen[MW] and Q_gen[MVar] attributes if your simulator follows the generator convention (i.e. generation is positive), and use the P_load[MW] and Q_load[MVar] attributes if your simulator follows the consumer convention (i.e. consumption is positive).

If your entity models a generator instead (i.e. it produces real power and maintains a fixed voltage level instead of a fixed reactive power), the process is slightly more involved. First, you need to create a ControlledGen entity at the bus that you want to control, by calling

gen = pp_sim.ControlledGen(bus=bus_index)

where bus_index is the index of the bus where the generator should be connected. Then, you can connect your simulator to the gen entity.

Table of entity types and their attributes

The following table describes the model that this simulator supports, the attributes of these models, and whether they’re used as inputs or outputs.

Model	Attribute	In/Out	Description
Grid			meta entity representing the entire grid
Bus			a bus in the grid
	P_gen[MW]	In	real power in MW, following generator convention
	Q_gen[MVar]	In	reactive power in MVar, following generator convention
	P_load[MW]	In	real power in MW, following consumer convention
	Q_load[MVar]	In	reactive power in MVar, following consumer convention
	P[MW]	Out	entire real power at this bus
	Q[MVar]	Out	entire reactive power at this bus
	Vm[pu]	Out	voltage magnitude at this bus (in per unit)
	Va[deg]	Out	voltage angle at this bus (in degrees)
Load			an existing load in the grid
	P[MW]	Out	the real power consumed by this load
	Q[MVar]	Out	the reactive power consumed by this load
StaticGen			an existing static generator in the grid
	P[MW]	Out	the real power produced by this generator
	Q[MVar]	Out	the reactive power produced by this generator
Gen			an existing generator in the grid
	P[MW]	Out	the real power produced by this generator
	Q[MVar]	Out	the reactive power produced by this generator
	Vm[pu]	Out	the voltage magnitude this generator tries to hold
	Va[deg]	Out	the voltage angle for this generator
ControlledGen			a generator created by the user to control
Line			a line in the grid
	I[kA]	Out	the current along the line
	loading[%]	Out	the loading of the line

Development

For the development of this simulator, the following tools are employed:

• Hatch is used as a packaging manager. This offers the following commands:

  • hatch fmt to format the code (using ruff)
  • hatch run test:test to run pytest in a test matrix consisting of Python versions 3.9 and 3.11 and mosaik versions 3.2 and 3.3.0b1.
  • hatch run python for running Python.
  • hatch run to run arbitrary commands in the managed virtualenv.

  Also, we use hatch-vcs to automatically deduce version numbers from git tags. Adding a new tag starting with v on the main branch should automatically release this on PyPI.

• pre-commit is used to run hooks before committing and pushing. Install pre-commit (I recommend pipx) and install the hooks using pre-commit install.