pudl.analysis.fuel_by_plant#
Calculates useful FERC Form 1 fuel metrics on a per plant-year basis.
Module Contents#
Functions#
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Revert the filled nulls from string columns. |
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Revert the filled nulls from float columns. |
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Calculates useful FERC Form 1 fuel metrics on a per plant-year basis. |
- pudl.analysis.fuel_by_plant.revert_filled_in_string_nulls(df: pandas.DataFrame) pandas.DataFrame[source]#
Revert the filled nulls from string columns.
- pudl.analysis.fuel_by_plant.revert_filled_in_float_nulls(df: pandas.DataFrame) pandas.DataFrame[source]#
Revert the filled nulls from float columns.
- pudl.analysis.fuel_by_plant.fuel_by_plant_ferc1(fuel_df: pandas.DataFrame, fuel_categories: list[str], thresh: float = 0.5) pandas.DataFrame[source]#
Calculates useful FERC Form 1 fuel metrics on a per plant-year basis.
Each record in the FERC Form 1 corresponds to a particular type of fuel. Many plants – especially coal plants – use more than one fuel, with gas and/or diesel serving as startup fuels. In order to be able to classify the type of plant based on relative proportions of fuel consumed or fuel costs it is useful to aggregate these per-fuel records into a single record for each plant.
Fuel cost (in nominal dollars) and fuel heat content (in mmBTU) are calculated for each fuel based on the cost and heat content per unit, and the number of units consumed, and then summed by fuel type (there can be more than one record for a given type of fuel in each plant because we are simplifying the fuel categories). The per-fuel records are then pivoted to create one column per fuel type. The total is summed and stored separately, and the individual fuel costs & heat contents are divided by that total, to yield fuel proportions. Based on those proportions and a minimum threshold that’s passed in, a “primary” fuel type is then assigned to the plant-year record and given a string label.
- Parameters:
fuel_df – Pandas DataFrame resembling the post-transform result for the fuel_ferc1 table.
thresh – A value between 0.5 and 1.0 indicating the minimum fraction of overall heat content that must have been provided by a fuel in a plant-year for it to be considered the “primary” fuel for the plant in that year. Default value: 0.5.
- Returns:
DataFrame with a single record for each plant-year, including the columns required to merge it with the plants_steam_ferc1 table/DataFrame (report_year, utility_id_ferc1, and plant_name) as well as totals for fuel mmbtu consumed in that plant-year, and the cost of fuel in that year, the proportions of heat content and fuel costs for each fuel in that year, and a column that labels the plant’s primary fuel for that year.
- Raises:
AssertionError – If the DataFrame input does not have the columns required to run the function.