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International Journal of Photoenergy
Volume 2017, Article ID 1356851, 13 pages
https://doi.org/10.1155/2017/1356851
Review Article

Monitoring, Diagnosis, and Power Forecasting for Photovoltaic Fields: A Review

1Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
2Department of Génie Electrique, Faculty of Technologies, University of M’Sila, BP 166, Ichbelia, M’Sila, Algeria
3Department of Engineering and Architecture, University of Trieste, Piazzale Europa 1, 34127 Trieste, Italy
4Renewable Energy Laboratory, Faculty of Sciences and Technology, Jijel University, Jijel, Algeria
5School of Electronic, Electrical and Systems Engineering, University of Birmingham, Gisbert Kapp Building, Edgbaston, Birmingham B15 2TT, UK

Correspondence should be addressed to P. Guerriero; ti.aninu@oreirreug.igiulreip

Received 2 September 2016; Accepted 14 December 2016; Published 11 January 2017

Academic Editor: Wilfried G. J. H. M. Van Sark

Copyright © 2017 S. Daliento et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A wide literature review of recent advance on monitoring, diagnosis, and power forecasting for photovoltaic systems is presented in this paper. Research contributions are classified into the following five macroareas: (i) electrical methods, covering monitoring/diagnosis techniques based on the direct measurement of electrical parameters, carried out, respectively, at array level, single string level, and single panel level with special consideration to data transmission methods; (ii) data analysis based on artificial intelligence; (iii) power forecasting, intended as the ability to evaluate the producible power of solar systems, with emphasis on temporal horizons of specific applications; (iv) thermal analysis, mostly with reference to thermal images captured by means of unmanned aerial vehicles; (v) power converter reliability especially focused on residual lifetime estimation. The literature survey has been limited, with some exceptions, to papers published during the last five years to focus mainly on recent developments.