Dropout and Pruned Neural Networks for Fault Classification in Photovoltaic Arrays

Automatic detection of solar array faults reduces maintenance costs and increases efficiency. In this paper, we address the problem of fault detection, localization, and classification in utility-scale photovoltaic (PV) arrays using machine learning methods. More specifically, we develop a series of...

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Autors principals:	Sunil Rao, Gowtham Muniraju, Cihan Tepedelenlioglu, Devarajan Srinivasan, Govindasamy Tamizhmani, Andreas Spanias
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2021-01-01
Col·lecció:	IEEE Access
Matèries:	Dropout neural networks machine learning photovoltaic panel fault detection pruned neural networks solar array fault classification
Accés en línia:	https://ieeexplore.ieee.org/document/9525102/
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