@misc{4d3ee9eb27de4bc5bd8b0362fede3dfe,
title = "PV Degradation Modeling: Applying Geospatial Workflows with {"}PVDeg{"}",
abstract = "Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.",
keywords = "degradation, DURAMAT, geospatial, GitHub, high performance computing, modeling, open-source, photovoltaics, PVDeg, python, SAM, simulation",
author = "Tobin Ford and Silvana Ovaitt and Martin Springer and Michael Kempe",
year = "2025",
language = "American English",
series = "Presented at the Photovoltaic Reliability Workshop (PVRW), 4-6 March 2025, Golden, Colorado",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}