reV.handlers.transmission.POIFeatures

class POIFeatures(trans_table)[source]

Bases: TransmissionFeatures

Class that allows incremental connections to POI’s

Parameters:

trans_table (str | pandas.DataFrame) – Path to .csv or config file or DataFrame with supply curve transmission mapping. This table is only used to track remaining available capacity for connecting to POI’s. Must have the following columns:

  • “trans_gid”: Unique ID for every transmission feature

  • “ac_cap”: Available capacity for connection (in MW)

Methods

available_capacity(gid)

Get available capacity for given line

check_availability(gid)

Check availablity of feature with given gid

check_feature_dependencies()

Check features for dependencies that are missing and raise error.

connect(gid, capacity)

Check if you can connect to given feature If apply, update internal dictionary accordingly

cost(*__, **___)

Compute levelized cost of transmission (LCOT) for connecting to give feature

feature_capacity(trans_table[, avail_cap_frac])

Compute available capacity for all features
connect(gid, capacity)[source]

Check if you can connect to given feature If apply, update internal dictionary accordingly

Parameters:

  • gid (int) – Unique id of feature of interest

  • capacity (float) – Capacity needed in MW

  • apply (bool) – Apply capacity to feature with given gid and update internal dictionary

Returns:

connected (bool) – Flag as to whether connection is possible or not

cost(*__, **___)[source]

Compute levelized cost of transmission (LCOT) for connecting to give feature

Parameters:

  • gid (int) – Feature gid to connect to

  • distance (float) – Distance to feature in kms

  • line_multiplier (float) – Multiplier for region specific line cost increases

  • capacity (float) – Capacity needed in MW, if None DO NOT check if connection is possible

Returns:

cost (float) – Cost of transmission in $/MW, if None indicates connection is NOT possible

available_capacity(gid)

Get available capacity for given line

Parameters:

gid (int) – Unique id of feature of interest

Returns:

avail_cap (float) – Available capacity = capacity * available fraction default = 100%

check_availability(gid)

Check availablity of feature with given gid

Parameters:

gid (int) – Feature gid to check

Returns:

bool – Whether the gid is available or not

check_feature_dependencies()

Check features for dependencies that are missing and raise error.

classmethod feature_capacity(trans_table, avail_cap_frac=1)

Compute available capacity for all features

Parameters:

  • trans_table (str | pandas.DataFrame) – Path to .csv or .json containing supply curve transmission mapping

  • avail_cap_frac (float, optional) – Fraction of capacity that is available for connection, by default 1

Returns:

feature_cap (pandas.DataFrame) – Available Capacity for each transmission feature