Marmot_plot_select: csv file#

Select which plots to create. Set values to TRUE to create the specified plot.

Allows some customization on how the plot will appear, including:

  • Adding property annotations

  • Set max y-axis value

  • Set start and end dates

  • Specify timescale for timeseries plots

  • Adjust scenario Grouping

Since individual plots can be modified in several ways, copying of rows, and adjusting the Figure Output Name and other settings is permitted and encouraged. The following describes the layout of the input sheet.

Input Definitions#

Columns#

The Marmot_plot_select.csv has 14 columns:

  • Figure Output Name (required):

    The name given to the figure when saved as output. This name is user editable and can be adjusted as liked. Figures will be saved in the Figures_Output folder where the Marmot_Solutions_folder has been set in the Marmot_user_defined_inputs: csv file.

  • Plot Graph (required):

    Set to TRUE to plot the figure or FALSE to skip.

  • Plot Property (optional):

    Controls the addition of annotations or selection of certain data elements such as individual generator or line names. The following are the list of available annotations that can be applied to the specified plots:

    • gen_stack:

      • Peak Demand

      • Min Net Load

      • Peak RE

      • Peak Unserved Energy

      • Peak Curtailment

    • gen_unstack:

      • Min Net Load

      • Peak Demand

    • reserve_gen_timeseries:

      • Peak Reserve Provision

  • Y-Axis Max (optional):

    The maximum y-axis value. Currently only used in the price.py plots

  • Day Before (optional):

    Sets the number of days to include before the specified annotation in Plot Property. If timestamps data intervals are larger than hours the interval range will be used in place of Days. (e.g., if data interval is years, this is the equivalent of Year before)

  • Day After (optional):

    Sets the number of days to include after the specified annotation in Plot Property If timestamps data intervals are larger than hours, the interval range will be used in place of Days. (e.g., if data interval is years, this is the equivalent of Year before)

  • Timezone (optional):

    Optional time zone to apply to the figures x-axes

  • Start date (optional):

    The start date to plot data from. Accepts any of the following formats:

    • M/D/Y

    • M/Y

    • Y

    • M/D/Y HH:MM:SS

    It will also accept dates formatted as D/M/Y and Y/M/D. Python will make a best guess at the inputted format. If left blank the entire range of data will be plotted.

  • End date (optional):

    The end date to plot data to. Accepts any of the following formats:

    • M/D/Y

    • M/Y

    • Y

    • M/D/Y HH:MM:SS

    It will also accept dates formatted as D/M/Y and Y/M/D. Python will make a best guess at the inputted format. If left blank the entire range of data will be plotted.

    Note

    Setting a Start date and End Date is important when comparing results sets of differing timeseries horizon lengths. This is especially important when creating bar plots. Different horizon lengths commonly occur when comparing ReEDS vs PLEXOS results, which can cause value discrepancies particularly noticeable in Installed Capacity or Total Generation plots if date ranges do not align.

  • Timeseries Plot Resolution (optional):

    The resolution to plot timeseries figures at. Current available options are Interval and Annual. If the value is left blank and the plot creates a timeseries, Marmot will default to plotting interval data.

    New in version 0.10.0.

  • Group by Scenario or Year-Scenario (optional):

    Specifies whether to group data by Scenario or Year-Scenario. This setting will only effect data that has been grouped into bar plots or diurnal line plots and will have no effect on timeseries plots. If grouping by Year-Scenario the year will be identified from the input data timestamp and appended to the Scenarios name defined in Marmot_user_defined_inputs: csv file. This is useful when plotting data which covers multiple years such as ReEDS. If left blank Marmot will default to grouping data by Scenario.

    New in version 0.10.0.

  • Custom Data File (optional):

    Path to a custom data file allowing the insertion of custom columns that will be appended to the final data frame before plotting The custom data file must be a csv. Default position of new columns is at the end of the existing data frame. Custom data files should have the same format as the final output data csv’s, the usual format is scenarios in index, generator techs as column names. However, this format may not hold true for all plots in the future. Therefore, using this feature may involve some trial and error and should be considered experimental. Custom Data Files can be added into the following plots:

    • production_cost: prod_cost

    • production_cost: sys_cost

    • production_cost: detailed_gen_cost

    • production_cost : sys_cost_type

    • emissions : total_emissions_by_type

    New in version 0.9.0.

  • Marmot Module (required):

    The name of the module containing the plotting methods. Plotting modules group plots by type, e.g total_generation, prices, curtailment etc. This is a required value and should not be modified. Copying the data to a new line is permitted with the inclusion of the corresponding method.

  • Method (required):

    The name of the method containing the specific plot logic. These methods are contained within the corresponding module. This is a required value and should not be modified. Copying the data to a new line is permitted with the inclusion of the corresponding module.

Input Example#

For an example of the file see it on the GitHub repo: Marmot_plot_select