A supervised ensemble learning method for fault diagnosis in photovoltaic strings

Ceyhun Kapucu and Mete Cubukcu

Energy, 2021, vol. 227, issue C

Abstract: This study proposes a fault diagnosis method based on the use of a machine learning (ML) technique called ensemble learning (EL) for photovoltaic (PV) systems. EL methods aim to obtain better generalizability and prediction accuracy than a single ML algorithm by combining the predictions of multiple algorithms. In this context, first the most relevant features are selected by using grid-search with cross-validation. Then each learning algorithm and the EL model that will combine them have been improved in terms of parameter optimization.

Keywords: Photovoltaic monitoring; Fault diagnosis; Ensemble learning; Classification; Optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:227:y:2021:i:c:s036054422100712x

DOI: 10.1016/j.energy.2021.120463

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