cronian.demands

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

add_prosumer_demands(→ None)	Add the end_use demands of the prosumer to the optimization model.
add_prosumer_base_demand(→ None)	Add prosumer's base demand as Pyomo Param to the optimization model.
add_prosumer_flex_demands(→ None)	Add prosumer's flexible demand as Pyomo Var (with Cons) to the model.

Module Contents

cronian.demands.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.

cronian.demands.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.

cronian.demands.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.