cronian.prosumers
Function to build a prosumer’s optimization model from a yaml configuration.
Functions
Add all built prosumers to the optimization model. |
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Build prosumer's optim. model from prosumer dict and timeseries data. |
Module Contents
- cronian.prosumers.add_built_prosumers_to_optimization_model(model: pyomo.environ.AbstractModel, prosumers: dict[str, dict], timeseries_data: pandas.DataFrame, number_of_timesteps: int, storage_model: str) pyomo.environ.AbstractModel
Add all built prosumers to the optimization model.
- Parameters:
model – The Pyomo model to add components to.
prosumers – Dictionary containing all prosumers (excludes explicitly modeled prosumers).
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.
storage_model – Type of storage model to use: simple or complex.
- Returns:
Pyomo AbstractModel with all built prosumers added.
- cronian.prosumers.build_prosumer_model(model: pyomo.environ.AbstractModel, prosumer: dict, timeseries_data: pandas.DataFrame, number_of_timesteps: int, storage_model: str, init_store_levels: dict[str, float] = None) pyomo.environ.AbstractModel
Build prosumer’s optim. model from prosumer dict and timeseries data.
- Parameters:
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.
storage_model – Type of storage model to use: simple or complex.
init_store_levels – Amount of energy to initialize each end_use_demand store with from previously satisfied flexible demand.
- Returns:
Pyomo AbstractModel of the given prosumer with all components added.
- Raises:
ValueError – If an invalid storage model is provided. Must be ‘simple’ or ‘complex’.