@misc{fbd72938951a457496daff93a5348067,
title = "AI and ML Applications for PV Reliability and System Performance",
abstract = "This poster discusses AI and ML topics in PV reliability and system performance. In particular, automated metadata extraction and QA for fielded solar installations is covered for the PV Fleets Project. Additionally, statistical learning topics for the PVInsight Project are addressed, as well as development of the PV Validation Hub.",
keywords = "algorithm, analytics, deep learning, machine learning, solar",
author = "Kirsten Perry and Chris Deline and Dirk Jordan and Michael Deceglie and Matthew Muller and Martin Springer and Robert White and B. Meyers and D. Ragsdale and S. Miskovich and G. Ogut",
year = "2023",
language = "American English",
series = "Presented at the 2023 SETO Workshop on the Solar Applications of Artificial Intelligence and Machine Learning, 31 October - 1 November 2023, Alexandria, Virginia",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}