Fault Detection and Predictive Maintenance of Photovoltaic Facilities

Roberto G. Aragón (), Fernando Chacón-Gómez, M. Eugenia Cornejo (), Jesús Medina () and Eloísa Ramírez-Poussa ()
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Roberto G. Aragón: Department of Mathematics, University of Cádiz, Cádiz, Spain
Fernando Chacón-Gómez: Department of Mathematics, University of Cádiz, Cádiz, Spain
M. Eugenia Cornejo: Department of Mathematics, University of Cádiz, Cádiz, Spain
Jesús Medina: Department of Mathematics, University of Cádiz, Cádiz, Spain
Eloísa Ramírez-Poussa: Department of Mathematics, University of Cádiz, Cádiz, Spain

International Journal of Information Technology & Decision Making (IJITDM), 2025, vol. 24, issue 07, 1971-2003

Abstract: This paper introduces an automatic decision support system for photovoltaic fault detection and predictive maintenance without the use of meteorological variables, which is a remarkable feature due to the lack of weather forecasts and wide variety of cases. This system improves another previous methodology to fault detection and introduces for the first time a module to predictive maintenance with good results. This module is based on fuzzy sets and the modeling of the behavior of the facilities through the computation and selection of a set of decision rules. The new decision support system has been validated and tested in the facilities of the company Grupo Energético de Puerto Real S.A.

Keywords: Photovoltaic energy generation; faults detection; predictive maintenance; OWA operator; fuzzy sets (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0219622025500531

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