reV.supply_curve.competitive_wind_farms.CompetitiveWindFarms

class CompetitiveWindFarms(wind_dirs, sc_points, n_dirs=2, offshore=False)

Bases: object

Handle competitive wind farm exclusion during supply curve sorting

Parameters:

• wind_dirs (pandas.DataFrame | str) – path to .csv or reVX.wind_dirs.wind_dirs.WindDirs output with the neighboring supply curve point gids and power-rose value at each cardinal direction

• sc_points (pandas.DataFrame | str) – Supply curve point summary table

• n_dirs (int, optional) – Number of prominent directions to use, by default 2

• offshore (bool) – Flag as to whether offshore farms should be included during CompetitiveWindFarms

Methods

check_sc_gid(sc_gid)	Check to see if sc_gid is valid, if so return associated sc_point_gids
exclude_sc_point_gid(sc_point_gid)	Exclude supply curve point gid, return False if gid is not present in list of available gids to avoid key errors elsewhere
map_downwind(sc_point_gid)	Map given sc_point_gid to downwind neighbors
map_sc_gid_to_sc_point_gid(sc_gid)	Map given sc_gid to equivalent sc_point_gid
map_sc_point_gid_to_sc_gid(sc_point_gid)	Map given sc_point_gid to equivalent sc_gid(s)
map_upwind(sc_point_gid)	Map given sc_point_gid to upwind neighbors
remove_noncompetitive_farm(sc_points[, ...])	Remove neighboring sc points for given number of prominent wind directions
run(wind_dirs, sc_points[, n_dirs, ...])	Exclude given number of neighboring Supply Point gids based on most prominent wind directions

Attributes

mask	Supply curve point boolean mask, used for efficient exclusion False == excluded sc_point_gid
sc_gids	Un-masked sc_gids
sc_point_gids	Un-masked sc_point_gids

property mask

Supply curve point boolean mask, used for efficient exclusion False == excluded sc_point_gid

Returns:

ndarray

property sc_point_gids

Un-masked sc_point_gids

Returns:

ndarray

property sc_gids

Un-masked sc_gids

Returns:

ndarray

map_sc_point_gid_to_sc_gid(sc_point_gid)

Map given sc_point_gid to equivalent sc_gid(s)

Parameters:

sc_point_gid (int) – Supply curve point gid to map to equivalent supply curve gid(s)

Returns:

int | list – Equivalent supply curve gid(s)

map_sc_gid_to_sc_point_gid(sc_gid)

Map given sc_gid to equivalent sc_point_gid

Parameters:

sc_gid (int) – Supply curve gid to map to equivalent supply point curve gid

Returns:

int – Equivalent supply point curve gid

check_sc_gid(sc_gid)

Check to see if sc_gid is valid, if so return associated sc_point_gids

Parameters:

sc_gid (int) – Supply curve gid to map to equivalent supply point curve gid

Returns:

int | None – Equivalent supply point curve gid or None if sc_gid is invalid (offshore)

map_upwind(sc_point_gid)

Map given sc_point_gid to upwind neighbors

Parameters:

sc_point_gid (int) – Supply point curve gid to get upwind neighbors

Returns:

int | list – upwind neighborings

map_downwind(sc_point_gid)

Map given sc_point_gid to downwind neighbors

Parameters:

sc_point_gid (int) – Supply point curve gid to get downwind neighbors

Returns:

int | list – downwind neighborings

exclude_sc_point_gid(sc_point_gid)

Exclude supply curve point gid, return False if gid is not present in list of available gids to avoid key errors elsewhere

Parameters:

sc_point_gid (int) – supply curve point gid to mask

Returns:

bool – Flag if gid is valid and was masked

remove_noncompetitive_farm(sc_points, sort_on='total_lcoe', downwind=False)

Remove neighboring sc points for given number of prominent wind directions

Parameters:

• sc_points (pandas.DataFrame | str) – Supply curve point summary table

• sort_on (str, optional) – column to sort on before excluding neighbors, by default ‘total_lcoe’

• downwind (bool, optional) – Flag to remove downwind neighbors as well as upwind neighbors, by default False

Returns:

sc_points (pandas.DataFrame) – Updated supply curve points after removing non-competative wind farms

classmethod run(wind_dirs, sc_points, n_dirs=2, offshore=False, sort_on='total_lcoe', downwind=False, out_fpath=None)

Exclude given number of neighboring Supply Point gids based on most prominent wind directions

Parameters:

• wind_dirs (pandas.DataFrame | str) – path to .csv or reVX.wind_dirs.wind_dirs.WindDirs output with the neighboring supply curve point gids and power-rose value at each cardinal direction

• sc_points (pandas.DataFrame | str) – Supply curve point summary table

• n_dirs (int, optional) – Number of prominent directions to use, by default 2

• offshore (bool) – Flag as to whether offshore farms should be included during CompetitiveWindFarms

• sort_on (str, optional) – column to sort on before excluding neighbors, by default ‘total_lcoe’

• downwind (bool, optional) – Flag to remove downwind neighbors as well as upwind neighbors, by default False

• out_fpath (str, optional) – Path to .csv file to save updated sc_points to, by default None

Returns:

sc_points (pandas.DataFrame) – Updated supply curve points after removing non-competative wind farms