pypsa.optimization.optimize.OptimizationAccessor.create_model

pypsa.optimization.optimize.OptimizationAccessor.create_model#

OptimizationAccessor.create_model(snapshots=None, multi_investment_periods=False, transmission_losses=0, linearized_unit_commitment=False, **kwargs)#

Create a linopy.Model instance from a pypsa network.

The model is stored at n.model.

Parameters:

  • n (pypsa.Network)

  • snapshots (list or index slice) – A list of snapshots to optimise, must be a subset of network.snapshots, defaults to network.snapshots

  • multi_investment_periods (bool, default False) – Whether to optimise as a single investment period or to optimize in multiple investment periods. Then, snapshots should be a pd.MultiIndex.

  • transmission_losses (int, default 0)

  • linearized_unit_commitment (bool, default False) – Whether to optimise using the linearised unit commitment formulation or not.

  • **kwargs – Keyword arguments used by linopy.Model(), such as solver_dir or chunk.

Return type:

linopy.model

Contents