PVAnalytics: A Python Package for Automated Processing of Solar Time Series Data

Kirsten Perry, William Vining, Kevin Anderson, Matthew Muller, Cliff Hansen

Research output: NRELPresentation


Multiple publicly available software packages exist that analyze solar time series data, including RdTools and Solar Data Tools, among others. Several of these packages contain their own unique quality assurance (QA) and feature recognition algorithms. The python PVAnalytics package was developed to offer an internally consistent source for these analysis tools, making it easier for the end user to deploy these routines on his or her solar data. The PVAnalytics package currently contains routines for outlier detection, inverter clipping detection, irradiance and temperature checks, orientation checks, and data shift detection, among other functions. These functions have been aggregated from various sources including Solar Forecast Arbiter, RdTools, and the QA process developed by NREL's PV Fleets Initiative. We are continuously adding new functionality to the package, including documentation, examples and algorithms. By bundling QA functionality into a single software package, we hope to make PVAnalytics a comprehensive software library to support analysis of solar metadata and time series data.
Original languageAmerican English
Number of pages17
StatePublished - 2022

Publication series

NamePresented at the PV Performance Modeling and Monitoring Workshop, 23-24 August 2022, Salt Lake City, Utah

NREL Publication Number

  • NREL/PR-5K00-83824


  • data cleaning
  • pre-processing
  • python
  • quality assurance
  • quality control
  • solar


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