Mappings

In pandaprosumer, mappings allow to create connections between controllers in a prosumer, or between controller in a prosumer and in a controller in pandapower or pandapipes network.

Each mapping has an initiator controller and a responder controller

Mappings are executed at the end of the initiator controller control_step to map the relevant data to the input of the responder controller.

Generic Mapping

GenericMapping provides a flexible way to map numerical data between controllers. It allows adding or subtracting values from one controller’s step results to another controller’s inputs.

Controller interaction with Generic Mapping within prosumer

Key Features: - Supports both scalar and vector mappings. - Allows element-wise addition and subtraction operations. - Handles missing values with default replacements.

Implementation Details**

class pandaprosumer.mapping.generic.GenericMapping(container=None, initiator_id=None, initiator_column=None, responder_id=None, responder_column=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Generic mapping between controllers.

Map the data in initiator_column in the step results of the initiator to the responder_column input columns of the responder. initiator_column and responder_column can be strings or lists of strings of the same length

__init__(container=None, initiator_id=None, initiator_column=None, responder_id=None, responder_column=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Initializes the GenericWiseMapping.

Parameters:

• container – The prosumer object

• initiator_id – The initiating controller

• initiator_column – The column in the initiating controller (string or list of strings)

• responder_id – The responding controller

• responder_column – The column in the responding controller (string or list of strings)

• order – The order of mapping application

• application_operation – The operation to apply (default: “add”)

• weights – Weights for the mapping

• index – The index of the mapping

map(initiator_controller, responder_controller)

Applies the element-wise mapping between the initiator and responder controllers.

Parameters:

• initiator_controller – The initiating controller

• responder_controller – The responding controller

Methods and Functionalities

• _add_mapping(initiator_controller, responder_controller, initiator_column, responder_column)

  • Adds the values from the initiator controller’s result column to the responder controller’s input column.

  • Replaces NaN values with zero before applying the operation.

• _subtract_mapping(initiator_controller, responder_controller, initiator_column, responder_column)

  • Subtracts the values from the initiator controller’s result column from the responder controller’s input column.

  • Uses similar handling for NaN values as in _add_mapping.

• GenericMapping sets the argument no_chain=True by default. The no_chain attribute is a key flag that defines whether a mapping participates in controller chaining.

Fluid Mix Mapping

Fluid Mix Mapping in PandaProsumer is designed to perform mapping operations for fluid properties between controllers. Each prosumer controller is expected to maintain specific attributes for fluid data:

• input_mass_flow_with_temp: A dictionary containing the fluid’s temperature and mass flow.

• result_mass_flow_with_temp: A list of dictionaries (to allow one-to-many mappings) with computed fluid properties.

Controller interaction with Fluid Mix Mapping within prosumer

The FluidMixMapping operation performs the following steps: - Retrieves the initiator’s fluid properties (temperature and mass flow) from the result_mass_flow_with_temp list based on the specified order. - If the responder’s fluid input values (temperature or mass flow) are NaN, the initiator’s fluid properties are used directly. - Otherwise, it computes a new fluid state by:

• Summing the mass flows.

• Calculating the temperature as a weighted average. If the total mass flow is zero, the simple average of the temperatures is used.

• The resulting mixed fluid properties are stored back in the responder’s input_mass_flow_with_temp.

class pandaprosumer.mapping.fluid_mix.FluidMixMapping(container=None, initiator_id=None, responder_id=None, order=None, application_operation='add', weights=None, no_chain=False, index=None)

Fluid mapping between controllers.

Each prosumer controller has special input_mass_flow_with_temp and result_mass_flow_with_temp attributes.

input_mass_flow_with_temp is a dictionary containing the temperature and mass flow of the fluid

result_mass_flow_with_temp is a list of dictionaries (to allow 1 to many mapping)

__init__(container=None, initiator_id=None, responder_id=None, order=None, application_operation='add', weights=None, no_chain=False, index=None)

Initializes the GenericWiseMapping.

Parameters:

• container – The prosumer object

• initiator_id – The initiating controller

• responder_id – The responding controller

• order – The order of mapping application

• application_operation – The operation to apply (default: “add”)

• weights – Weights for the mapping

• index – The index of the mapping

map(initiator_controller, responder_controller)

Applies the element-wise mapping between the initiator and responder controllers.

Parameters:

• initiator_controller – The initiating controller

• responder_controller – The responding controller

• FluidMixMapping sets the argument no_chain=False by default. The no_chain attribute is a key flag that defines whether a mapping participates in controller chaining.

Generic Energy System Mapping

Generic Energy System Mapping enables mapping between controllers that belong to different prosumer networks or producers. This mapping extends the functionality of GenericMapping by allowing the responder controller to be located in a separate prosumer. The attribute responder_net represents the target prosumer, from which the responder controller is retrieved by its identifier.

class pandaprosumer.mapping.generic_energy_system.GenericEnergySystemMapping(container=None, initiator_id=None, initiator_column=None, responder_net=None, responder_id=None, responder_column=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Generic mapping between controllers in different containers.

Allows to map a variable to a responder controller in another container responder_net.

__init__(container=None, initiator_id=None, initiator_column=None, responder_net=None, responder_id=None, responder_column=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Initializes the GenericWiseMapping.

Parameters:

• container – The prosumer object

• initiator_id – The initiating controller

• initiator_column – The column in the initiating controller

• responder_id – The responding controller

• responder_column – The column in the responding controller

• order – The order of mapping application

• application_operation – The operation to apply (default: “add”)

• weights – Weights for the mapping

• index – The index of the mapping

map(initiator_controller, responder_controller_id)

Applies the element-wise mapping between the initiator and responder controllers.

Parameters:

• initiator_controller – The initiating controller

• responder_controller_id – The responding controller id in the mapping’s responder_net

Fluid Mix Energy System Mapping

Fluid Mix Energy System Mapping enables mapping between controllers that belong to different prosumer networks or producers. This mapping extends the functionality of FluidMixMapping by allowing the responder controller to be located in a separate prosumer. The attribute responder_net represents the target prosumer, from which the responder controller is retrieved by its identifier.

class pandaprosumer.mapping.fluid_mix_energy_system.FluidMixEnergySystemMapping(container=None, initiator_id=None, responder_net=None, responder_id=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Fluid Mix mapping between controllers in different networks/producers.

__init__(container=None, initiator_id=None, responder_net=None, responder_id=None, order=None, application_operation='add', weights=None, no_chain=True, index=None)

Initializes the GenericWiseMapping.

Parameters:

• container – The prosumer object

• initiator_id – The initiating controller

• responder_id – The responding controller

• order – The order of mapping application

• application_operation – The operation to apply (default: “add”)

• weights – Weights for the mapping

• index – The index of the mapping

map(initiator_controller, responder_controller_id)

Applies the element-wise mapping between the initiator and responder controllers.

Parameters:

• initiator_controller – The initiating controller

• responder_controller_id – The responding controller id in the mapping’s responder_net

Order of Mapping vs Controller Order

It is important to distinguish between the order attribute in mappings and the order of controllers:

• Mapping `order`:

  • Defines the sequence in which mappings are applied for a given initiator controller.

  • When a controller has multiple responder mappings, the order ensures that mappings are executed in a predictable and controlled order.

  • This is especially relevant in fluid mixing scenarios, where the final state of a responder depends on the accumulation of multiple mappings.

  Note

  The mapping order is local to the initiator. Each initiator can have mappings with order = 0, 1, 2, …, controlling the order in which its mappings are applied to different responders.

• Controller `order`:

  • Defines the execution order of controllers themselves during the simulation.

  • Controllers are calculated in order of their order attribute during each simulation step, regardless of any mapping logic.

Key Differences

Concept	What It Controls
Mapping order	Order of mapping applications per initiator
Controller order	Execution sequence of controllers globally

These two types of order do not influence each other directly, but together they allow for precise control over the flow and transformation of data within and across controllers.