annular.market.tulipa.run_model
===============================

.. py:module:: annular.market.tulipa.run_model


Attributes
----------

.. autoapisummary::

   annular.market.tulipa.run_model.logger


Functions
---------

.. autoapisummary::

   annular.market.tulipa.run_model.run_julia_subprocess
   annular.market.tulipa.run_model.run_market_model


Module Contents
---------------

.. py:data:: logger

.. py:function:: run_julia_subprocess(tulipa_config: annular.market.tulipa.config._TulipaConfig) -> None

   Run Julia subprocess with Tulipa configuration.

   :param tulipa_config: :class:`_TulipaConfig` instance with paths and settings.

   :raises RuntimeError: If Julia subprocess fails with non-zero exit code.


.. py:function:: run_market_model(bids: pandas.DataFrame, timeseries_data: pandas.DataFrame, snapshots: pandas.DatetimeIndex, bidding_window: pandas.DatetimeIndex, output_path: pathlib.Path, iteration_id: int, config: dict) -> tuple[numpy.ndarray, numpy.ndarray]

   Create the central market clearing model.

   :param bids: MultiIndex DataFrame of bids for all satellites.
   :param timeseries_data: DataFrame with timeseries_data for entire simulation time.
   :param snapshots: Optimization window of the market model.
   :param bidding_window: Bidding window that matters for bids.
   :param output_path: Path to store the database file with the solved `TulipaEnergyModel`.
                       The file is named `tulipa_iteration-ID.duckdb` where `ID` is
                       the iteration ID (starting at 0).
   :param iteration_id: Identifier of the iteration number. Used internally to
                        manage folder names.
   :param config: config dict

   :returns: market clearing price and quantities allocated by the market.
   :rtype: tuple

   :raises ValueError: If Tulipa configuration is incomplete.
   :raises RuntimeError: - if Tulipa cofiguration caused other problems
       - if the optimization problem is infeasible or unbounded