Simplifying Geospatial Workflows for PV Modeling with GeoGridFusion

Growing demands to understand photovoltaic (PV) deployment and reliability across an expanding range of climates, along with increasing computational power, are driving the need for simplified computing tools that support large-scale analysis and geospatial workflows. While existing open-source libraries and PV system modeling tools offer extensive collections of empirical and physical models, they often lack the ability to scale to large geospatial datasets. The tool presented here, GeoGridFusion, enables PV modelers to store and utilize gridded geospatial data from sources such as NSRDB, PVGIS, and others. GeoGridFusion harmonizes diverse datasets, taxonomies, and nomenclatures, and includes utilities that support intuitive geospatial area selection.

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Published
2025-06-08
DOI
https://doi.org/10.1109/pvsc59419.2025.11132420
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Simplifying Geospatial Workflows for PV Modeling with GeoGridFusion

Silvana Ovaitt, Michael Kempe, Martin Springer, Yazan J.K. Musleh et al.
Distributed and Parallel Computing Systems
article

Simplifying Geospatial Workflows for PV Modeling with GeoGridFusion

Silvana Ovaitt, Michael Kempe, Martin Springer, Yazan J.K. Musleh, Tobin Ford
article en

Abstract

Growing demands to understand photovoltaic (PV) deployment and reliability across an expanding range of climates, along with increasing computational power, are driving the need for simplified computing tools that support large-scale analysis and geospatial workflows. While existing open-source libraries and PV system modeling tools offer extensive collections of empirical and physical models, they often lack the ability to scale to large geospatial datasets. The tool presented here, GeoGridFusion, enables PV modelers to store and utilize gridded geospatial data from sources such as NSRDB, PVGIS, and others. GeoGridFusion harmonizes diverse datasets, taxonomies, and nomenclatures, and includes utilities that support intuitive geospatial area selection.

National Laboratory of the Rockies (US), Colorado School of Mines (US), University of Southampton (GB)
U.S. Department of Energy, Office of Energy, Solar Energy Technologies Office, National Renewable Energy Laboratory
Openalex Percentile: Top 74%
Distributed and Parallel Computing Systems
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Simplifying Geospatial Workflows for PV Modeling with GeoGridFusion — Silvana Ovaitt, Michael Kempe, et al. · (2025) | TGRS Research Map | TGRS