marmot.formatters.formatreeds.ProcessReEDS#

class ProcessReEDS(input_folder: pathlib.Path, output_file_path: pathlib.Path, *args, process_subset_years: typing.Optional[list] = None, region_mapping: pandas.core.frame.DataFrame = Empty DataFrame Columns: [] Index: [], **kwargs)[source]#

Bases: marmot.formatters.formatbase.Process

Process ReEDS specific data from a ReEDS result set.

Parameters

input_folder (Path) – Folder containing csv files.
output_file_path (Path) – Path to formatted h5 output file.
process_subset_years (list, optional) – If provided only process years specified. Defaults to None.
region_mapping (pd.DataFrame, optional) – DataFrame to map custom regions/zones to create custom aggregations. Defaults to pd.DataFrame().
**kwargs – These parameters will be passed to the Process class.

Methods

`df_process_generator`(df[, prop, gdx_file])	Does any additional processing for generator properties
`df_process_line`(df[, prop, gdx_file])	Does any additional processing for line properties
`df_process_reserves_generators`(df[, prop, ...])	Does any additional processing for reserves_generators properties
`get_processed_data`(prop_class, prop, ...)	Handles the pulling of data from the ReEDS gdx file and then passes the data to one of the formating functions
`merge_timeseries_block_data`(df)	Merge chronological time intervals with reeds timeslices
`output_metadata`(files_list)	Add ReEDS specific metadata to formatted h5 file .

Attributes

`GDX_RESULTS_PREFIX`	Prefix of gdx results file
`PROPERTY_MAPPING`	Maps simulation model property names to Marmot property names
`UNITS_CONVERSION`	Dictionary to convert units to standard values used by Marmot
`data_collection`	Dictionary input file names to full filename path
`get_input_data_paths`	Gets a list of input gdx files within the scenario folders
`input_folder`	Path to input folder
`property_units`	Gets the property units from data, e.g MW, MWh
`reeds_prop_cols`	Get the ReEDSPropertyColumns dataclass
`wind_resource_to_pca`	Get the wind resource (s) to pca/region mapping

PROPERTY_MAPPING: dict = {'emission_emit_r': 'emission_Production', 'generator_cap_out': 'generator_Installed_Capacity', 'generator_curt_out': 'generator_Curtailment', 'generator_gen_out': 'generator_Generation', 'generator_gen_out_ann': 'generator_Generation_Annual', 'generator_stor_in': 'generator_Pump_Load', 'generator_systemcost_techba': 'generator_Total_Generation_Cost', 'line_losses_tran_h': 'line_Losses', 'line_tran_flow_power': 'line_Flow', 'line_tran_out': 'line_Import_Limit', 'region_load_rt': 'region_Demand', 'reserves_generators_opRes_supply': 'reserves_generators_Provision_Annual', 'reserves_generators_opRes_supply_h': 'reserves_generators_Provision', 'storage_stor_energy_cap': 'storage_Max_Volume'}#: Maps simulation model property names to Marmot property names

GDX_RESULTS_PREFIX = 'rep_'#: Prefix of gdx results file

EXTRA_PROPERTIES_CLASS#: alias of marmot.formatters.formatextra.ExtraReEDSProperties

property reeds_prop_cols: marmot.formatters.formatreeds.ReEDSPropertyColumns#

Get the ReEDSPropertyColumns dataclass

Returns: ReEDSPropertyColumns

property property_units: dict#

Gets the property units from data, e.g MW, MWh

Returns: property_units
Return type: dict

property wind_resource_to_pca: dict#

Get the wind resource (s) to pca/region mapping

Returns: wind_resource_to_pca mapping
Return type: dict

property get_input_data_paths: list#: Gets a list of input gdx files within the scenario folders

property data_collection: Dict[str, pathlib.Path]#

Dictionary input file names to full filename path

Returns: data_collection {filename: fullpath}
Return type: dict

output_metadata(files_list: list) → None[source]#

Add ReEDS specific metadata to formatted h5 file .

Parameters: files_list (list) – List of all gdx files in inputs folder in alpha numeric order.

get_processed_data(prop_class: str, prop: str, timescale: str, model_name: str) → pandas.core.frame.DataFrame[source]#

Handles the pulling of data from the ReEDS gdx file and then passes the data to one of the formating functions

Parameters

prop_class (str) – Property class e.g Region, Generator, Zone etc
prop (str) – Property e.g gen_out, cap_out etc.
timescale (str) – Data timescale, e.g interval, summary.
model_name (str) – name of model to process.

Returns

Formatted results dataframe.

Return type

pd.DataFrame

merge_timeseries_block_data(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]#

Merge chronological time intervals with reeds timeslices

Parameters: df (pd.DataFrame) – input dataframe
Returns: df with merged in timeseries data
Return type: pd.DataFrame

df_process_generator(df: pandas.core.frame.DataFrame, prop: Optional[str] = None, gdx_file: Optional[str] = None) → pandas.core.frame.DataFrame[source]#

Does any additional processing for generator properties

Parameters

df (pd.DataFrame) – input dataframe
prop (str, optional) – ReEDS input property. Defaults to None.
gdx_file (str, optional) – String path to GDX file. Defaults to None.

Return type

pd.DataFrame

df_process_line(df: pandas.core.frame.DataFrame, prop: Optional[str] = None, gdx_file: Optional[str] = None) → pandas.core.frame.DataFrame[source]#

Does any additional processing for line properties

Parameters

df (pd.DataFrame) – input dataframe
prop (str, optional) – ReEDS input property. Defaults to None.
gdx_file (str, optional) – String path to GDX file. Defaults to None.

Return type

pd.DataFrame

df_process_reserves_generators(df: pandas.core.frame.DataFrame, prop: Optional[str] = None, gdx_file: Optional[str] = None) → pandas.core.frame.DataFrame[source]#

Does any additional processing for reserves_generators properties

Parameters

df (pd.DataFrame) – input dataframe
prop (str, optional) – ReEDS input property. Defaults to None.
gdx_file (str, optional) – String path to GDX file. Defaults to None.

Return type

pd.DataFrame