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

Conference · Wed Sep 07 04:00:00 EDT 2022

OSTI ID:1887283

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

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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1887283
• Report Number(s): NREL/PR-5K00-83824; MainId:84597; UUID:11885dc2-a32b-4dd8-9d05-aa723210649c; MainAdminID:65323
• Country of Publication: United States
• Language: English

Related Subjects

MATHEMATICS AND COMPUTING
SOLAR ENERGY
data cleaning
pre-processing
python
quality assurance
quality control
solar