PVAnalytics is a python library that supports analytics for PV systems. It provides functions for quality control, filtering, and feature labeling and other tools supporting the analysis of PV system-level data.
PVAnalytics is available at PyPI
and can be installed using pip
:
pip install pvanalytics
Documentation and example usage is available at pvanalytics.readthedocs.io.
The functions provided by PVAnalytics are organized in modules based
on their anticipated use. The structure/organization below is likely
to change as use cases are identified and refined and as package
content evolves. The functions in quality
and
features
take a series of data and return a series of booleans.
For more detailed descriptions, see our
API Reference.
-
quality
contains submodules for different kinds of data quality checks.data_shifts
contains quality checks for detecting and isolating data shifts in PV time series data.irradiance
provides quality checks for irradiance measurements.weather
has quality checks for weather data (for example tests for physically plausible values of temperature, wind speed, humidity, etc.)outliers
contains different functions for identifying outliers in the data.gaps
contains functions for identifying gaps in the data (i.e. missing values, stuck values, and interpolation).time
quality checks related to time (e.g. timestamp spacing)util
general purpose quality functions.
-
features
contains submodules with different methods for identifying and labeling salient features.clipping
functions for labeling inverter clipping.clearsky
functions for identifying periods of clear sky conditions.daytime
functions for for identifying periods of day and night.orientation
functions for labeling data as corresponding to a rotating solar tracker or a fixed tilt structure.shading
functions for identifying shadows.
-
system
identification of PV system characteristics from data (e.g. nameplate power, orientation, azimuth) -
metrics
contains functions for computing PV system-level metrics