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DOE OSTI · 3022271

A Public Data Set of Auto-Generated Geotagged PV Site Equipment, Generated via Deep Learning

Perry, Kirsten [National Laboratory of the Rockies (NLR), Golden, CO (United States)]·Nguyen, Quyen [National Laboratory of the Rockies (NLR), Golden, CO (United States)]·Ruby, Marwan [National Laboratory of the Rockies (NLR), Golden, CO (United States)]
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Abstract

In this research, we present a data set over 100 photovoltaic (PV) sites in TX, which have been automatically geotagged via a fully autonomous deep learning (DL) pipeline. Specifically, locations of inverters, tracker/fixed tilt rows, batteries, and substations are labeled algorithmically. To ensure high data quality, all systems have been reviewed manually and any deep learning errors have been corrected. This public data set, as well as the open-sourced pipeline used to generate it, is valuable for site planning, modelling, and insurance purposes. Given time and resources, we hope to extend the data set to additional states/regions in the US.

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14 SOLAR ENERGYcomputer visiondeep learningphotovoltaicsatellite imagerysite geotagging

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Perry, Kirsten [National Laboratory of the Rockies (NLR), Golden, CO (United States)], Nguyen, Quyen [National Laboratory of the Rockies (NLR), Golden, CO (United States)], Ruby, Marwan [National Laboratory of the Rockies (NLR), Golden, CO (United States)]. 2026-02-24. A Public Data Set of Auto-Generated Geotagged PV Site Equipment, Generated via Deep Learning. https://doi.org/10.21948/3022271

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