pvOps: a Python package for empirical analysis of photovoltaic field data

Journal Article · 15 November 2023 · Journal of Open Source Software

DOI: https://doi.org/10.21105/joss.05755 · OSTI ID:2311477

Bonney, Kirk Layne  ^[1]; Gunda, Thushara  ^[1]; Hopwood, Michael W.  ^[2]; Mendoza, Hector  ^[1]; Jackson, Nicole Danielle  ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Univ. of Central Florida, Orlando, FL (United States)

The purpose of pvOps is to support empirical evaluations of data collected in the field related to the operations and maintenance (O&M) of photovoltaic (PV) power plants. pvOps presently contains modules that address the diversity of field data, including text-based maintenance logs, current-voltage (IV) curves, and timeseries of production information. The package functions leverage machine learning, visualization, and other techniques to enable cleaning, processing, and fusion of these datasets. These capabilities are intended to facilitate easier evaluation of field patterns and extraction of relevant insights to support reliability-related decision-making for PV sites. The open-source code, examples, and instructions for installing the package through PyPI can be accessed through the GitHub repository.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office; USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: NA0003525
• OSTI ID: 2311477
• Report Number(s): SAND--2023-13746J
• Journal Information: Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 91 Vol. 8; ISSN 2475-9066
• Publisher: Open Source Initiative - NumFOCUSCopyright Statement
• Country of Publication: United States
• Language: English