Detect if a System is Tracking

Identifying if a system is tracking or fixed tilt

It is valuable to identify if a system is fixed tilt or tracking for future analysis. This example shows how to use pvanalytics.system.is_tracking_envelope() to determine if a system is tracking or not by fitting data to a maximum power or irradiance envelope, and fitting this envelope to quadratic and quartic curves. The r^2 output from these fits is used to determine if the system fits a tracking or fixed-tilt profile.

import pvanalytics
from pvanalytics.system import is_tracking_envelope
from pvanalytics.features.clipping import geometric
from pvanalytics.features.daytime import power_or_irradiance
import pandas as pd
import pathlib
import matplotlib.pyplot as plt

First, we import an AC power data stream from the SERF East site located at NREL. This data set is publicly available via the PVDAQ database in the DOE Open Energy Data Initiative (OEDI) (https://data.openei.org/submissions/4568), under system ID 50. This data is timezone-localized. This particular data stream is associated with a fixed-tilt system.

pvanalytics_dir = pathlib.Path(pvanalytics.__file__).parent
ac_power_file = pvanalytics_dir / 'data' / \
    'serf_east_15min_ac_power.csv'
data = pd.read_csv(ac_power_file, index_col=0, parse_dates=True)
data = data.sort_index()
time_series = data['ac_power']
time_series = time_series.asfreq('15min')

# Plot the first few days of the time series to visualize it
time_series[:pd.to_datetime("2016-07-06 00:00:00-07:00")].plot()
plt.show()

Run the clipping and the daytime filters on the time series. Both of these masks will be used as inputs to the pvanalytics.system.is_tracking_envelope() function.

# Generate the daylight mask for the AC power time series
daytime_mask = power_or_irradiance(time_series)

# Generate the clipping mask for the time series
clipping_mask = geometric(time_series)

Now, we use pvanalytics.system.is_tracking_envelope() to identify if the data stream is associated with a tracking or fixed-tilt system.

predicted_mounting_config = is_tracking_envelope(time_series,
                                                 daytime_mask,
                                                 clipping_mask)

print("Estimated mounting configuration: " + predicted_mounting_config.name)

Estimated mounting configuration: FIXED

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