Solar

class enflow.assets.solar.FixedMount(surface_tilt: float = 0.0, surface_azimuth: float = 0.0)

Bases: object

surface_tilt: float = 0.0

surface_azimuth: float = 0.0

class enflow.assets.solar.SingleAxisTrackerMount(axis_tilt: float = 0.0, axis_azimuth: float = 0.0, max_angle: float | tuple = 90.0, backtrack: bool = True, gcr: float = 0.2857142857142857, cross_axis_tilt: float = 0.0, racking_model: str | None = None, module_height: float | None = None)

Bases: object

axis_tilt: float = 0.0

axis_azimuth: float = 0.0

max_angle: float | tuple = 90.0

backtrack: bool = True

gcr: float = 0.2857142857142857

cross_axis_tilt: float = 0.0

racking_model: str | None = None

module_height: float | None = None

class enflow.assets.solar.PVArray(capacity: float | None = None, surface_azimuth: float | None = None, surface_tilt: float | None = None, surface_area: float | None = None, efficiency: float | None = None, module: str | None = None, module_type: str = 'glass_polymer', module_parameters: dict | pandas.core.series.Series = None, temperature_model_parameters: dict | pandas.core.series.Series = None, *, name: str | None = None, location: energydatamodel.geospatial.GeoLocation | None = None, latitude: float | None = None, longitude: float | None = None, altitude: float | None = None, tz: timezone | None = None, timeseries: energydatamodel.base.TimeSeries | None = None)

Bases: EnergyAsset

capacity: float | None = None

surface_azimuth: float | None = None

surface_tilt: float | None = None

surface_area: float | None = None

efficiency: float | None = None

module: str | None = None

module_type: str = 'glass_polymer'

module_parameters: dict | Series = None

temperature_model_parameters: dict | Series = None

get_timeseries()

altitude: t.Optional[float] = None

geometry_to_geojson(geometry)

get_location()

latitude: t.Optional[float] = None

location: t.Optional[Location] = None

longitude: t.Optional[float] = None

name: t.Optional[str] = None

plot_timeseries(start_date: str | DatetimeIndex | None = None, end_date: str | DatetimeIndex | None = None) → Axes

Plots a pandas Series using its built-in plot method.

Args:

start_date: The start date for the plot. end_date: The end date for the plot.

Returns:

The Matplotlib Axes object of the plot.

timeseries: t.Optional[TimeSeries] = None

to_dataframe()

Convert data class to a pandas DataFrame.

to_geojson(exclude_none=True)

to_json(include_none: bool = False) → str

tz: t.Optional[pytz.timezone] = None

class enflow.assets.solar.PVSystem(pv_arrays: ~typing.List[~energydatamodel.solar.PVArray] = <factory>, capacity: float = None, surface_azimuth: float = None, surface_tilt: float = None, albedo: float | None = None, surface_type: str | None = None, module_parameters: dict | None = None, inverter_parameters: dict | None = None, module_type: str = 'glass_polymer', racking_model: str = 'open_rack', *, name: str | None = None, location: ~energydatamodel.geospatial.GeoLocation | None = None, latitude: float | None = None, longitude: float | None = None, altitude: float | None = None, tz: ~pytz.timezone | None = None, timeseries: ~energydatamodel.base.TimeSeries | None = None)

Bases: EnergyAsset

The PVSystem class defines a standard set of PV system attributes and modeling functions. This class describes the collection and interactions of PV system components rather than an installed system on the ground. It is typically used in combination with Location and ModelChain objects.

pv_arrays: List[PVArray]

capacity: float = None

surface_azimuth: float = None

surface_tilt: float = None

albedo: float | None = None

surface_type: str | None = None

module_parameters: dict | None = None

inverter_parameters: dict | None = None

module_type: str = 'glass_polymer'

racking_model: str = 'open_rack'

to_pvlib(**kwargs)

altitude: t.Optional[float] = None

geometry_to_geojson(geometry)

get_location()

latitude: t.Optional[float] = None

location: t.Optional[Location] = None

longitude: t.Optional[float] = None

name: t.Optional[str] = None

plot_timeseries(start_date: str | DatetimeIndex | None = None, end_date: str | DatetimeIndex | None = None) → Axes

Plots a pandas Series using its built-in plot method.

Args:

start_date: The start date for the plot. end_date: The end date for the plot.

Returns:

The Matplotlib Axes object of the plot.

timeseries: t.Optional[TimeSeries] = None

to_dataframe()

Convert data class to a pandas DataFrame.

to_geojson(exclude_none=True)

to_json(include_none: bool = False) → str

tz: t.Optional[pytz.timezone] = None

class enflow.assets.solar.SolarPowerArea(capacity: float | pandas.core.frame.DataFrame = None, geopolygon: energydatamodel.geospatial.GeoPolygon | energydatamodel.geospatial.GeoMultiPolygon = None, *, name: str | None = None, location: energydatamodel.geospatial.GeoLocation | None = None, latitude: float | None = None, longitude: float | None = None, altitude: float | None = None, tz: timezone | None = None, timeseries: energydatamodel.base.TimeSeries | None = None)

Bases: EnergyAsset

capacity: float | DataFrame = None

geopolygon: GeoPolygon | GeoMultiPolygon = None

to_geojson()

property geojson

altitude: t.Optional[float] = None

geometry_to_geojson(geometry)

get_location()

latitude: t.Optional[float] = None

location: t.Optional[Location] = None

longitude: t.Optional[float] = None

name: t.Optional[str] = None

plot_timeseries(start_date: str | DatetimeIndex | None = None, end_date: str | DatetimeIndex | None = None) → Axes

Plots a pandas Series using its built-in plot method.

Args:

start_date: The start date for the plot. end_date: The end date for the plot.

Returns:

The Matplotlib Axes object of the plot.

timeseries: t.Optional[TimeSeries] = None

to_dataframe()

Convert data class to a pandas DataFrame.

to_json(include_none: bool = False) → str

tz: t.Optional[pytz.timezone] = None