Optimisation ================= The optimisation module allows for an optimisation of the energy system using a cost function with can consist of monetary or carbon cost or a combination of the two quantities. The optimisation relies on using a LP or MILP optimizer accessed via the energy system optimization framework Calliope (Pfenninger & Pickering, 2018). Via Calliope, a solver, such as Gurobi, is accessed. The optimisation happens using the methods built into the optimizer. The more technologies are present in the energy system, the longer the optimisation takes. Activating integer variables (i.e. the asynchronous storage) leads to significantly longer optimisation times. In addition to the conventional optimisation mode, a pareto front mode is also available. In this mode, a monetary-co2 pareto front is constructed. The parameters of the optimisation are .. include:: ../how_to_use_the_model/input_csv_as_rst/optimisation.rst References ----------- Pfenninger, S., & Pickering, B. (2018). *Calliope: a multi-scale energy systems modelling framework.* Journal of Open Source Software, 3(29), 825. |Pfenninger2018_DOI_link| .. |Pfenninger2018_DOI_link| raw:: html https://doi.org/10.21105/joss.00825