2.2 Using pvlib.iotools helper functions to get Solcast data

Introduction¶

In this notebook we fetch Solcast radiation and weather data using the pvlib.iotools helper function, and then directly feed this data into a pvlib ModelChain.

Imports¶

In [1]:

import pvlib
from matplotlib import pyplot as plt

import os; YOUR_SOLCAST_API_KEY_HERE = os.environ["API_KEY"]

import pvlib from matplotlib import pyplot as plt import os; YOUR_SOLCAST_API_KEY_HERE = os.environ["API_KEY"]

Fetch Solcast Data¶

pvlib has the following helper functions to fetch Solcast API data into a format immediately usable by pvlib:

• pvlib.iotools.get_solcast_forecast
• pvlib.iotools.get_solcast_live
• pvlib.iotools.get_solcast_historic
• pvlib.iotools.get_solcast_tmy

In [2]:

# unmetered location Goodwin Creek [SURFRAD], won't consume API requests
location = pvlib.location.Location(latitude=34.2547, longitude=-89.8729)

# unmetered location Goodwin Creek [SURFRAD], won't consume API requests location = pvlib.location.Location(latitude=34.2547, longitude=-89.8729)

In [3]:

# makes a call to https://api.solcast.com.au/data/historic/radiation_and_weather
weather_df, metadata = pvlib.iotools.get_solcast_historic(
    location.latitude, location.longitude,
    start="2024-07-09T00:00-07:00", end="2024-07-11T00:00-07:00",
    output_parameters=[
        # these will be converted from Solcast API names (https://docs.solcast.com.au)
        # to PVLIB convention (https://pvlib-python.readthedocs.io/en/stable/user_guide/variables_style_rules.html)
        # names and units.
        "ghi", "dni", "dhi", "air_temp", "wind_speed_10m"
    ],
    period="PT15M",
    api_key=YOUR_SOLCAST_API_KEY_HERE,
)
weather_df = weather_df.tz_convert("-07:00")
display(weather_df.head())

# makes a call to https://api.solcast.com.au/data/historic/radiation_and_weather weather_df, metadata = pvlib.iotools.get_solcast_historic( location.latitude, location.longitude, start="2024-07-09T00:00-07:00", end="2024-07-11T00:00-07:00", output_parameters=[ # these will be converted from Solcast API names (https://docs.solcast.com.au) # to PVLIB convention (https://pvlib-python.readthedocs.io/en/stable/user_guide/variables_style_rules.html) # names and units. "ghi", "dni", "dhi", "air_temp", "wind_speed_10m" ], period="PT15M", api_key=YOUR_SOLCAST_API_KEY_HERE, ) weather_df = weather_df.tz_convert("-07:00") display(weather_df.head())

	temp_air	dhi	dni	ghi	wind_speed
period_mid
2024-07-09 00:07:30-07:00	25	0	0	0	4.4
2024-07-09 00:22:30-07:00	25	0	0	0	4.4
2024-07-09 00:37:30-07:00	25	0	0	0	4.4
2024-07-09 00:52:30-07:00	25	0	0	0	4.4
2024-07-09 01:07:30-07:00	25	0	0	0	4.4

In [4]:

weather_df.plot(
    subplots=True, figsize=(7,7), 
    title="Solcast API Weather Data\nGoodwin Creek, Mississippi", 
    xlabel="UTC -07:00"
)
plt.show()

weather_df.plot( subplots=True, figsize=(7,7), title="Solcast API Weather Data\nGoodwin Creek, Mississippi", xlabel="UTC -07:00" ) plt.show()

pvlib power model¶

Here we pick some sensible defaults for a simple 10kW AC, 12kW DC fixed-tilt PV system.

We calculate the power production for east, south, west and north facings to show the different power profiles under these circumstances.

In [5]:

for panel_azimuth, facing_label in [(0, "N"), (90, "E"), (180, "S"), (-90, "W")]:
    system = pvlib.pvsystem.PVSystem(
        surface_tilt=30, 
        surface_azimuth=panel_azimuth,
        # pvwatts, DC capacity = 12 kW
        module_parameters={"pdc0": 12, "gamma_pdc": -0.003},
        # pvwatts, AC capacity = 10 kW
        inverter_parameters={"pdc0": 10/0.98, "eta_inv_nom": 0.98},
        temperature_model_parameters=pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS['sapm']['open_rack_glass_glass'],
    )
    model_chain = pvlib.modelchain.ModelChain(system, location, aoi_model="no_loss", spectral_model="no_loss")
    model_chain.run_model(weather_df)
    model_chain.results.ac.plot(label=facing_label, xlabel="UTC -07:00", ylabel="kW")

plt.title("PVlib Models with Solcast Weather Data\nGoodwin Creek, Mississippi")
plt.legend(title="panel facings")
plt.show()

for panel_azimuth, facing_label in [(0, "N"), (90, "E"), (180, "S"), (-90, "W")]: system = pvlib.pvsystem.PVSystem( surface_tilt=30, surface_azimuth=panel_azimuth, # pvwatts, DC capacity = 12 kW module_parameters={"pdc0": 12, "gamma_pdc": -0.003}, # pvwatts, AC capacity = 10 kW inverter_parameters={"pdc0": 10/0.98, "eta_inv_nom": 0.98}, temperature_model_parameters=pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS['sapm']['open_rack_glass_glass'], ) model_chain = pvlib.modelchain.ModelChain(system, location, aoi_model="no_loss", spectral_model="no_loss") model_chain.run_model(weather_df) model_chain.results.ac.plot(label=facing_label, xlabel="UTC -07:00", ylabel="kW") plt.title("PVlib Models with Solcast Weather Data\nGoodwin Creek, Mississippi") plt.legend(title="panel facings") plt.show()