RdTools is an open-source library to support reproducible technical analysis of time series data from photovoltaic energy systems. The library aims to provide best practice analysis routines along with the building blocks for users to tailor their own analyses. Current applications include the evaluation of PV production over several years to obtain rates of performance degradation and soiling loss. RdTools can handle both high frequency (hourly or better) or low frequency (daily, weekly, etc.) datasets. Best results are obtained with higher frequency data.
RdTools can be installed automatically into Python from PyPI using the command line:
pip install rdtools
For API documentation and full examples, please see the documentation.
RdTools currently is tested on Python 3.6+.
The underlying workflow of RdTools has been published in several places. If you use RdTools in a published work, please cite the following as appropriate:
The clear sky temperature calculation,
clearsky_temperature.get_clearsky_tamb(), uses data
from images created by Jesse Allen, NASA’s Earth Observatory using data courtesy of the MODIS Land Group.
Other useful references which may also be consulted for degradation rate methodology include:
Check out the wiki for additional usage documentation, and for information on development goals and framework.