cronian.demands
===============

.. py:module:: cronian.demands

.. autoapi-nested-parse::

   Functions to add prosumer's demands to the optimization model.

   It currently contains the following functions:
       - add_prosumer_demands
       - add_prosumer_base_demand
       - add_prosumer_flex_demands



Functions
---------

.. autoapisummary::

   cronian.demands.add_prosumer_demands
   cronian.demands.add_prosumer_base_demand
   cronian.demands.add_prosumer_flex_demands


Module Contents
---------------

.. py:function:: add_prosumer_demands(model: pyomo.environ.AbstractModel, prosumer: dict, timeseries_data: pandas.DataFrame, number_of_timesteps: int, end_use_demand: str, init_store_level: float = 0) -> None

   Add the end_use demands of the prosumer to the optimization model.

   Args:
       model: The Pyomo model to add components to.
       prosumer: Dictionary containing prosumer details.
       timeseries_data: Timeseries data containing the availability factors for
           VRE generators and EVs doing V2G, demand profiles for prosumers, ...
       number_of_timesteps: Number of timesteps to run the optimization for.
       end_use_demand: Name of end_use demand, e.g., space_heating.
       init_store_level: Amount of energy to initialize the store with from
           previously satisfied flexible demand.


.. py:function:: add_prosumer_base_demand(model: pyomo.environ.AbstractModel, prosumer: dict, timeseries_data: pandas.DataFrame, number_of_timesteps: int, end_use_demand: str) -> None

   Add prosumer's base demand as Pyomo Param to the optimization model.

   Args:
       model: Pyomo Abstract model.
       prosumer:  Dictionary containing prosumer details.
       timeseries_data: Timeseries data containing the availability factors for
           VRE generators, demand profiles of prosumers, etc.
       number_of_timesteps: Number of timesteps to run the optimization for.
       end_use_demand: Name of end_use demand, e.g., space_heating.


.. py:function:: add_prosumer_flex_demands(model: pyomo.environ.AbstractModel, prosumer: dict, timeseries_data: pandas.DataFrame, number_of_timesteps: int, end_use_demand: str, init_store_level: float = 0) -> None

   Add prosumer's flexible demand as Pyomo Var (with Cons) to the model.

   Flexible demand is modeled as a store, with constraints on its energy level
   feasible region (e_min and e_max) and energy level consistency.

   If `init_store_level` is given, the energy level feasible region is shifted
   down by the specified amount, with any resulting negative values for `e_min`
   set to 0.

   Args:
       model: Pyomo Abstract model.
       prosumer:  Dictionary containing prosumer details.
       timeseries_data: Timeseries data containing the availability factors for
           VRE generators, demand profiles of prosumers, etc.
       number_of_timesteps: Number of timesteps to run the optimization for.
       end_use_demand: Name of end_use demand (electricity_for_space_heating).
       init_store_level: Amount of energy to initialize the store with from
           previously satisfied flexible demand.