Design and Development of an Online Smart Monitoring and Diagnosis System for Photovoltaic Distributed Generation

Thiago A. Felipe, Fernando C. Melo and Luiz C. G. Freitas
Additional contact information
Thiago A. Felipe: Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlândia 38400-902, Brazil
Fernando C. Melo: Electrical Engineering Department, University of Brasilia, Brasília 70910-900, Brazil
Luiz C. G. Freitas: Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlândia 38400-902, Brazil

Energies, 2021, vol. 14, issue 24, 1-13

Abstract: In photovoltaic power plants, fault diagnosis tools are essential for ensuring a high energy yield. These tools should be capable of accurately identifying and quantifying the factors behind the various fault mechanisms commonly found in photovoltaic plants. Considering the aforementioned factors, this article proposes an online smart PV monitoring solution, which is capable of detecting malfunctions that arise from accidental and/or technical causes through the analysis of I-V curves, however, without the necessity to interrupt the operation of the system, thus reducing the maintenance cost. Accidental causes can lead to the reduction of energy productivity due to the excessive accumulation of dirt on the photovoltaic modules, partial shading and eventual errors that occur during its installation. On the other hand, technical causes can be attributed to faults found on the photovoltaic modules, which lead to gradual losses in their electric and material characteristics. Therefore, by using the electric characteristics supplied by the manufacturer of the installed modules, the I-V and P-V curves of the operational photovoltaic strings were obtained in real time, compared to the respective theoretical curves obtained through mathematical modeling. In order to validate the proposed online monitoring system and its potential for predictive maintenance application, a field experimentation was mounted in a 93.8 kWp photovoltaic system.

Keywords: energy management; PV data analytics and diagnostics; PV predictive maintenance; smart PV monitoring solutions; software-as-a-service (SaaS); solar energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/24/8552/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/24/8552/ (text/html)

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:gam:jeners:v:14:y:2021:i:24:p:8552-:d:705827

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().