PowerAnalytics

Re-categorizes data according to an aggregation dictionary

• makes no guarantee of complete data collection *

Example

aggregation = PA.make_fuel_dictionary(results_uc.system)
categorize_data(gen_uc.data, aggregation)

generators = make_fuel_dictionary(system::PSY.System, mapping::Dict{NamedTuple, String})

This function makes a dictionary of fuel type and the generators associated.

Arguments

• sys::PSY.System: the system that is used to create the results
• results::IS.Results: results

Key Words

• categories::Dict{String, NamedTuple}: if stacking by a different category is desired

Example

results = solveopmodel!(OpModel) generators = makefueldictionary(sys)

aggregates and combines data into single DataFrame

Example

PG.combine_categories(gen_uc.data)

Return the generator category for this fuel and unit_type.

Return a dict where keys are a tuple of input parameters (fuel, unit_type) and values are generator types.