Skip to the main content

Original scientific paper

https://doi.org/10.32985/ijeces.15.3.2

Real-Time Fault Identification of Photovoltaic Systems Based on Remote Monitoring with IoT

Fernando Jacome orcid id orcid.org/0000-0001-5960-0228 ; Instituto Tecnológico Superior Rumiñahui, Electricity Career Sangolquí, Ecuador
Luis Daniel Andagoya-Alba ; Instituto Tecnológico Superior Rumiñahui, Electricity Career Sangolquí, Ecuador *
Henry Osorio orcid id orcid.org/0000-0001-6407-1076 ; Instituto Tecnológico Superior Rumiñahui, Electricity Career Sangolquí, Ecuador
Edison Paredes orcid id orcid.org/0009-0000-3124-070X ; Instituto Tecnológico Superior Rumiñahui, Electricity Career Sangolquí, Ecuador

* Corresponding author.


Full text: english pdf 3.040 Kb

page 225-234

downloads: 238

cite


Abstract

The increase in energy demand, as well as the need to protect the environment, has led to the promotion of new forms of generation, including photovoltaic energy. In this scenario, new challenges arise in the field of real-time monitoring of the characteristic variables of this type of system to determine correct operation. This paper presents the methodology of remote monitoring to detect faults in real-time in a photovoltaic system, taking advantage of the variables values that can be obtained from it, and estimating an operating state based on the behavior of these variables. The study used IoT technology for remote data acquisition, and by analyzing them, an estimate of the panel's operating status was made in real time by comparing the values of the variables registered. The study resulted in a real-time remote monitoring system that allows the estimation of the state of operation of a photovoltaic system and the classification of different types of failures that could occur in it. The study concludes that complex monitoring systems can be configured in real-time by technology based on IoT and with an adequate treatment of these variables, it is possible to estimate the photovoltaic systems' state of operation and identify electrical failures in them.

Keywords

Photovoltaic System; Faults; IoT; Electrical Variables;

Hrčak ID:

315393

URI

https://hrcak.srce.hr/315393

Publication date:

19.3.2024.

Visits: 641 *