annular.market

Submodules

• annular.market.base
• annular.market.tulipa

Attributes

market_models

Functions

run_base(→ tuple[numpy.ndarray, numpy.ndarray])	Run market model.
run_tulipa(→ tuple[numpy.ndarray, numpy.ndarray])	Create the central market clearing model.

Package Contents

annular.market.run_base(bids: pandas.DataFrame, generator_configs: dict[str, dict], timeseries_data: pandas.DataFrame, snapshots: pandas.DatetimeIndex, output_path: pathlib.Path) → tuple[numpy.ndarray, numpy.ndarray]

Run market model.

annular.market.run_tulipa(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.

Parameters:

• bids – MultiIndex DataFrame of bids for all satellites.

• timeseries_data – DataFrame with timeseries_data for entire simulation time.

• snapshots – Optimization window of the market model.

• bidding_window – Bidding window that matters for bids.

• 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).

• iteration_id – Identifier of the iteration number. Used internally to manage folder names.

• config – config dict

Returns:

market clearing price and quantities allocated by the market.

Return type:

tuple

Raises:

• ValueError – If Tulipa configuration is incomplete.

• RuntimeError –

  • if Tulipa cofiguration caused other problems

  • if the optimization problem is infeasible or unbounded

annular.market.market_models