Failure mode prediction and energy forecasting of PV plants to assist dynamic maintenance tasks by ANN based models

Fernando A. Olivencia Polo, Jesús Ferrero Bermejo, Juan F. Gómez Fernández and Adolfo Crespo Márquez

Renewable Energy, 2015, vol. 81, issue C, 227-238

Abstract: In the field of renewable energy, reliability analysis techniques combining the operating time of the system with the observation of operational and environmental conditions, are gaining importance over time.

Keywords: Renewable energy; Maintenance; Condition based maintenance; Artificial neural network; Proportional Weibull reliability (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148115002050
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:81:y:2015:i:c:p:227-238

DOI: 10.1016/j.renene.2015.03.023

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().