reVX.plexos.simple_plant_builder.SimplePlantBuilder

class SimplePlantBuilder(plant_meta, rev_sc, cf_fpath, forecast_fpath=None, plant_name_col=None, tech_tag=None, timezone='UTC', share_resource=True, max_workers=None, sc_mean_cf_col='mean_cf', sc_cap_col='capacity', dset_tag=None, bespoke=False)

Bases: BaseProfileAggregation

Class to build generation profiles for “plants” by aggregating resource from nearest neighbor supply curve points.

Run plexos aggregation.

Parameters:

• plant_meta (str | pd.DataFrame) – Str filepath or extracted dataframe for plant meta data with every row representing a plant with columns for latitude, longitude, and capacity (in MW). Plants will compete for available capacity in the reV supply curve input and will be prioritized based on the row order of this input.

• rev_sc (str | pd.DataFrame) – reV supply curve or sc-aggregation output table including sc_gid, latitude, longitude, res_gids, gid_counts, mean_cf.

• cf_fpath (str) – File path to capacity factor file (reV gen output) to get profiles from.

• forecast_fpath (str | None) – Forecasted capacity factor .h5 file path (reV results). If not None, the generation profiles are sourced from this file.

• plant_name_col (str | None) – Column in plexos_table that has the plant name that should be used in the plexos output csv column headers.

• tech_tag (str | None) – Optional technology tag to include as a suffix in the plexos output csv column headers.

• timezone (str) – Timezone for output generation profiles. This is a string that will be passed to pytz.timezone() e.g. US/Pacific, US/Mountain, US/Central, US/Eastern, or UTC. For a list of all available timezones, see pytz.all_timezones

• share_resource (bool) – Flag to share available capacity within a single resource GID between multiple plants.

• max_workers (int | None) – Max workers for parallel profile aggregation. None uses all available workers. 1 will run in serial.

• sc_mean_cf_col (str) – Mean capacity factor column name in the rev_sc table

• sc_cap_col (str) – Supply curve point capacity column name in the rev_sc table

• dset_tag (str) – Dataset tag to append to dataset names in cf profile file. e.g. If the cf profile file is a multi year file using dset_tag=”-2008” will enable us to select the corresponding datasets (cf_mean-2008, cf_profile-2008, etc)

• bespoke (bool) – Flag to signify if the cf_fpath file was generated using the reV bespoke wind module. The bespoke output files have generation profiles at the supply curve grid resolution which is different than traditional reV generation outputs that are on the resource grid resolution.

Methods

assign_plant_buildouts()	March through the plant meta data and make subsets of the supply curve table that will be built out for each plant.
check_valid_buildouts(plant_sc_builds)	Check that plant buildouts are mapped to valid resource data that can be found in the cf_fpath input.
convert_bespoke_sc(df, gid_column)	Convert a bespoke supply curve table to reference resource gids (res_gids) based on the bespoke generation outputs that are on the supply curve grid not the resource grid
export(meta, time_index, profiles, out_fpath)	Export generation profiles to h5 and plexos-formatted csv
get_unique_plant_names(table, name_col[, ...])	Get a list of ordered unique plant names
make_profiles(plant_sc_builds)	Make a 2D array of aggregated plant gen profiles.
run(plant_meta, rev_sc, cf_fpath[, ...])	Build profiles and meta data.
tz_convert_profiles(profiles, timezone)	Convert profiles to local time and forward/back fill missing data.

Attributes

available_res_gids	Resource gids available in the cf file.
forecast_map	An array mapping the reV "actuals" generation data to forecast data of a different resolution (if input).
node_map	Nearest neighbor output mapping rev supply curve points to plants or plexos nodes.
plant_meta	Get plant meta data for the requested plant buildout with buildout information
time_index	Get the generation profile time index.
tz_alias	Get a short 3-char tz alias if the timezone is common in the US (pst, mst, cst, est)

property plant_meta

Get plant meta data for the requested plant buildout with buildout information

Returns:

pd.DataFrame

assign_plant_buildouts()

March through the plant meta data and make subsets of the supply curve table that will be built out for each plant. The supply curve table attribute of this SimplePlantBuilder instance will be manipulated such that total sc point capacity and resource gid capacity is reduced whenever a plant is built. In this fashion, resource in SC points will not be double counted, but resource within an SC point can be divided up between multiple plants. Resource within an SC point is prioritized by available capacity.

Returns:

plant_sc_builds (dict) – Dictionary mapping the plant row indices (keys) to subsets of the SC table showing what should be built for each plant. The subset SC tables in this dict will no longer match the sc table attribute of the SimplePlantBuilder instance, because the tables in this dict show what should be built, and the sc table attribute will show what is remaining.

check_valid_buildouts(plant_sc_builds)

Check that plant buildouts are mapped to valid resource data that can be found in the cf_fpath input.

make_profiles(plant_sc_builds)

Make a 2D array of aggregated plant gen profiles.

Returns:

profiles (np.ndarray) – (t, n) array of plant eneration profiles where t is the timeseries length and n is the number of plants.

property available_res_gids

Resource gids available in the cf file.

Returns:

res_gids (np.ndarray) – Array of resource GIDs available in the cf file.

static convert_bespoke_sc(df, gid_column)

Convert a bespoke supply curve table to reference resource gids (res_gids) based on the bespoke generation outputs that are on the supply curve grid not the resource grid

Parameters:

• table (pd.DataFrame) – rev_sc and reeds_build inner joined on supply curve gid.

• gid_column (str) – String to use for sc_gid.

Returns:

table (pd.DataFrame) – Modified so that the “res_gids” points to the supply curve gids in the bespoke file so that the resource generation profiles will be taken based on the bespoke indexing.

export(meta, time_index, profiles, out_fpath)

Export generation profiles to h5 and plexos-formatted csv

Parameters:

• plant_meta (pd.DataFrame) – Plant / plexos node meta data with built capacities and mappings to the resource used.

• time_index (pd.datetimeindex) – Time index for the profiles.

• profiles (np.ndarray) – Generation profile timeseries in MW at each plant / plexos node.

• out_fpath (str, optional) – Path to .h5 file into which plant buildout should be saved. A plexos-formatted csv will also be written in the same directory. By default None.

property forecast_map

An array mapping the reV “actuals” generation data to forecast data of a different resolution (if input). This is an (n, 1) array where n is the number of “actuals” generation data points. So self.forecast_map[9] yields the forecast index that corresponds to index 9 in the cf_fpath reV generation output.

Returns:

np.ndarray | None

static get_unique_plant_names(table, name_col, tech_tag=None)

Get a list of ordered unique plant names

Parameters:

• table (pd.DataFrame) – Plexos / plant meta data table where every row is a plant

• name_col (str) – Column label in table. Exception will be raised if not found.

• tech_tag (str) – Technology tag to append to plant names like “pv” or “wind”

Returns:

names (list | None) – List of unique plant names

property node_map

Nearest neighbor output mapping rev supply curve points to plants or plexos nodes.

Returns:

np.ndarray

classmethod run(plant_meta, rev_sc, cf_fpath, forecast_fpath=None, plant_name_col=None, tech_tag=None, timezone='UTC', share_resource=True, max_workers=None, out_fpath=None, sc_mean_cf_col='mean_cf', sc_cap_col='capacity', dset_tag=None, bespoke=False)

Build profiles and meta data.

Parameters:

• plant_meta (str | pd.DataFrame) – Str filepath or extracted dataframe for plant meta data with every row representing a plant with columns for latitude, longitude, and capacity (in MW). Plants will compete for available capacity in the reV supply curve input and will be prioritized based on the row order of this input.

• rev_sc (str | pd.DataFrame) – reV supply curve or sc-aggregation output table including sc_gid, latitude, longitude, res_gids, gid_counts, mean_cf.

• cf_fpath (str) – File path to capacity factor file (reV gen output) to get profiles from.

• forecast_fpath (str | None) – Forecasted capacity factor .h5 file path (reV results). If not None, the generation profiles are sourced from this file.

• plant_name_col (str | None) – Column in plexos_table that has the plant name that should be used in the plexos output csv column headers.

• tech_tag (str | None) – Optional technology tag to include as a suffix in the plexos output csv column headers.

• timezone (str) – Timezone for output generation profiles. This is a string that will be passed to pytz.timezone() e.g. US/Pacific, US/Mountain, US/Central, US/Eastern, or UTC. For a list of all available timezones, see pytz.all_timezones

• share_resource (bool) – Flag to share available capacity within a single resource GID between multiple plants.

• max_workers (int | None) – Max workers for parallel profile aggregation. None uses all available workers. 1 will run in serial.

• out_fpath (str, optional) – Path to .h5 file into which plant buildout should be saved. A plexos-formatted csv will also be written in the same directory. By default None.

• sc_mean_cf_col (str) – Mean capacity factor column name in the rev_sc table

• sc_cap_col (str) – Supply curve point capacity column name in the rev_sc table

• dset_tag (str) – Dataset tag to append to dataset names in cf profile file. e.g. If the cf profile file is a multi year file using dset_tag=”-2008” will enable us to select the corresponding datasets (cf_mean-2008, cf_profile-2008, etc)

• bespoke (bool) – Flag to signify if the cf_fpath file was generated using the reV bespoke wind module. The bespoke output files have generation profiles at the supply curve grid resolution which is different than traditional reV generation outputs that are on the resource grid resolution.

Returns:

• plant_meta (pd.DataFrame) – Plant meta data with built capacities and mappings to the resource used.

• time_index (pd.datetimeindex) – Time index for the profiles.

• profiles (np.ndarray) – Generation profile timeseries in MW at each plant.

property time_index

Get the generation profile time index.

Returns:

time_index (pd.Datetimeindex) – Pandas datetime index sourced from the capacity factor data.

property tz_alias

Get a short 3-char tz alias if the timezone is common in the US (pst, mst, cst, est)

Returns:

str

static tz_convert_profiles(profiles, timezone)

Convert profiles to local time and forward/back fill missing data.

Parameters:

• profiles (np.ndarray) – Profiles of shape (time, n_plants) in UTC

• timezone (str) – Timezone for output generation profiles. This is a string that will be passed to pytz.timezone() e.g. US/Pacific, US/Mountain, US/Central, US/Eastern, or UTC. For a list of all available timezones, see pytz.all_timezones

Returns:

profiles (np.ndarray) – Profiles of shape (time, n_plants) in timezone