Optimize

Wrapping the oemof optimization process.

tessif_oemof_4_4.optimize.optimize(energy_system, solver='cbc', **kwargs)[source]

Optimize oemof system model

Parameters
  • energy_system (EnergySystem) – Oemof energy system to be simulated.

  • solver (str, default='cbc') –

    String specifying the solver to be used. For FOSS application, this is usually either cbc or glpk.

    But since pyomo is used for interfacing the solver. Any of it’s supported solvers can be used.

    Note

    In case the link above is servered, use the pyomo cli command:

    pyomo help --solvers
    

  • kwargs

    Keywords parameterizing the solver used as well as the energy system transformation process.

    Use one of solve's parameters for tweaking the solver.

Returns

optimized_es – Energy system carrying the optimization results.

Return type

EnergySystem