marmot.plottingmodules.unserved_energy.UnservedEnergy#

class UnservedEnergy(Zones: List[str], Scenarios: List[str], AGG_BY: str, ordered_gen: List[str], marmot_solutions_folder: pathlib.Path, custom_xticklabels: Optional[List[str]] = None, color_list: list = ['#396AB1', '#CC2529', '#3E9651', '#ff7f00', '#6B4C9A', '#922428', '#cab2d6', '#6a3d9a', '#fb9a99', '#b15928'], **kwargs)[source]#

Bases: marmot.plottingmodules.plotutils.plot_data_helper.PlotDataStoreAndProcessor

System unserved energy plots.

The unserved_energy.py module contains methods that are related to unserved energy in the power system.

UnservedEnergy inherits from the PlotDataStoreAndProcessor class to assist in creating figures.

Parameters

  • Zones (List[str]) – List of regions/zones to plot.

  • Scenarios (List[str]) – List of scenarios to plot.

  • AGG_BY (str) – Informs region type to aggregate by when creating plots.

  • ordered_gen (List[str]) – Ordered list of generator technologies to plot, order defines the generator technology position in stacked bar and area plots.

  • marmot_solutions_folder (Path) – Directory containing Marmot solution outputs.

  • custom_xticklabels (List[str], optional) – List of custom x labels to apply to barplots. Values will overwite existing ones. Defaults to None.

  • color_list (list, optional) – List of colors to apply to non-gen plots. Defaults to ColorList().colors.

Methods

average_diurnal_ue([start_date_range, ...])

Creates a line plot of average diurnal unserved energy.

tot_unserved_energy([start_date_range, ...])

Creates a bar plot of total unserved energy.

unserved_energy_timeseries([...])

Creates a timeseries line plot of total unserved energy.
unserved_energy_timeseries(start_date_range: Optional[str] = None, end_date_range: Optional[str] = None, data_resolution: str = '', **_)[source]#

Creates a timeseries line plot of total unserved energy.

Each sceanrio is plotted as a separate line.

Parameters

  • start_date_range (str, optional) – Defines a start date at which to represent data from. Defaults to None.

  • end_date_range (str, optional) – Defines a end date at which to represent data to. Defaults to None.

  • data_resolution (str, optional) –

    Specifies the data resolution to pull from the formatted data and plot. Defaults to “”, which will pull interval data.

    New in version 0.10.0.

Returns

Dictionary containing the created plot and its data table.

Return type

dict

tot_unserved_energy(start_date_range: Optional[str] = None, end_date_range: Optional[str] = None, scenario_groupby: str = 'Scenario', **_)[source]#

Creates a bar plot of total unserved energy.

Each sceanrio is plotted as a separate bar.

Parameters

  • start_date_range (str, optional) – Defines a start date at which to represent data from. Defaults to None.

  • end_date_range (str, optional) – Defines a end date at which to represent data to. Defaults to None.

  • scenario_groupby (str, optional) –

    Specifies whether to group data by Scenario or Year-Sceanrio. If grouping by Year-Sceanrio the year will be identified from the timestamp and appeneded to the sceanrio name. This is useful when plotting data which covers multiple years such as ReEDS. Defaults to Scenario.

    New in version 0.10.0.

Returns

Dictionary containing the created plot and its data table.

Return type

dict

average_diurnal_ue(start_date_range: Optional[str] = None, end_date_range: Optional[str] = None, scenario_groupby: str = 'Scenario', **_)[source]#

Creates a line plot of average diurnal unserved energy.

Each scenario is plotted as a separate line and shows the average hourly unserved energy over a 24 hour period averaged across the entire year or time period defined.

Parameters

  • start_date_range (str, optional) – Defines a start date at which to represent data from. Defaults to None.

  • end_date_range (str, optional) – Defines a end date at which to represent data to. Defaults to None.

  • scenario_groupby (str, optional) –

    Specifies whether to group data by Scenario or Year-Sceanrio. If grouping by Year-Sceanrio the year will be identified from the timestamp and appeneded to the sceanrio name. This is useful when plotting data which covers multiple years such as ReEDS. Defaults to Scenario.

    New in version 0.10.0.

Returns

Dictionary containing the created plot and its data table.

Return type

dict