Public API Reference

Reads in all the data stored in csv files in a directory

Arguments

• directory::AbstractString: directory containing CSV files
• base_power::Float64: base power for the PowerSystems.System
• user_descriptor_file::AbstractString: customized input descriptor file. Example
• descriptor_file=POWER_SYSTEM_DESCRIPTOR_FILE: PowerSystems.jl descriptor file. Default
• generator_mapping_file=GENERATOR_MAPPING_FILE_CDM: generator mapping configuration file. Default
• timeseries_metadata_file = joinpath(directory, "timeseries_pointers"): Time series pointers .json file. Example

The general format for data in the directory is:

• bus.csv (required)
  • columns specifying area and zone will create a corresponding set of Area and LoadZone objects.
  • columns specifying max_active_power or max_reactive_power will create PowerLoad objects when nonzero values are encountered and will contribute to the peak_active_power and peak_reactive_power values for the corresponding LoadZone object.
• branch.csv
• dc_branch.csv
• gen.csv
• load.csv
• reserves.csv
• storage.csv

Custom construction of generators

Each generator will be defined as a concrete subtype of PowerSystems.Generator, based on the fuel and type columns in gen.csv and the generator_mapping_file. The default mapping file is src/parsers/generator_mapping.yaml. You can override this behavior by specifying your own file.

Custom Column names

PowerSystems provides am input mapping capability that allows you to keep your own column names. For example, when parsing raw data for a generator the code expects a column called name. If the raw data instead defines that column as GEN UID then you can change the custom_name field under the generator category to GEN UID in your YAML file.

To enable the parsing of a custom set of csv files, you can generate a configuration file (such as user_descriptors.yaml) from the defaults, which are stored in src/descriptors/power_system_inputs.json.

python ./bin/generate_config_file.py ./user_descriptors.yaml

Next, edit this file with your customizations.

Note that the user-specific customizations are stored in YAML rather than JSON to allow for easier editing. The next few sections describe changes you can make to this YAML file. Do not edit the default JSON file.

Per-unit conversion

PowerSystems defines whether it expects a column value to be per-unit system base, per-unit device base, or natural units in power_system_inputs.json. If it expects a per-unit convention that differs from your values then you can set the unit_system in user_descriptors.yaml and PowerSystems will automatically convert the values. For example, if you have a max_active_power value stored in natural units (MW), but power_system_inputs.json specifies unit_system: device_base, you can enter unit_system: natural_units in user_descriptors.yaml and PowerSystems will divide the value by the value of the corresponding entry in the column identified by the base_reference field in power_system_inputs.json. You can also override the base_reference setting by adding base_reference: My Column to make device base per-unit conversion by dividing the value by the entry in My Column. System base per-unit conversions always divide the value by the system base_power value instantiated when constructing a System.

PowerSystems provides a limited set of unit conversions. For example, if power_system_inputs.json indicates that a value's unit is degrees but your values are in radians then you can set unit: radian in your YAML file. Other valid unit entries include GW, GWh, MW, MWh, kW, and kWh.

Examples

data_dir = "/data/my-data-dir"
base_power = 100.0
descriptors = "./user_descriptors.yaml"
timeseries_metadata_file = "./timeseries_pointers.json"
generator_mapping_file = "./generator_mapping.yaml"
data = PowerSystemTableData(
    data_dir,
    base_power,
    descriptors;
    timeseries_metadata_file = timeseries_metadata_file,
    generator_mapping_file = generator_mapping_file,
)
sys = System(data; time_series_in_memory = true)