Simulation-Based Fault Detection Remote Monitoring System for Small-Scale Photovoltaic Systems

Hee-Won Lim, Il-Kwon Kim, Ji-Hyeon Kim and U-Cheul Shin ()
Additional contact information
Hee-Won Lim: Department of Architectural Engineering, Daejeon University, Daejeon 34520, Republic of Korea
Il-Kwon Kim: Department of Architectural Engineering, Daejeon University, Daejeon 34520, Republic of Korea
Ji-Hyeon Kim: Department of Architectural Engineering, Daejeon University, Daejeon 34520, Republic of Korea
U-Cheul Shin: Department of Architectural Engineering, Daejeon University, Daejeon 34520, Republic of Korea

Energies, 2022, vol. 15, issue 24, 1-12

Abstract: A small-scale grid-connected PV system that is easy to install and is inexpensive as a remote monitoring system may cause economic losses if its failure is not found and it is left unattended for a long time. Thus, in this study, we developed a low-cost fault detection remote monitoring system for small-scale grid-connected PV systems. This active monitoring system equipped with a simulation-based fault detection algorithm accurately predicts AC power under normal operating conditions and notifies its failure when the measured power is abnormally low. In order to lower the cost, we used a single board computer (SBC) with edge computing as a data server and designed a monitoring system using openHAB, an open-source software. Additionally, we used the Shewhart control chart as a fault detection criterion and the ratio between the measured and predicted ac power for the normal operation data as an observation. As a result of the verification test for the actual grid-connected PV system, it was confirmed that the developed remote monitoring system was able to accurately identify the system failures in real-time, such as open circuit, short circuit, partial shading, etc.

Keywords: PV system; monitoring system; Shewhart control chart (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/24/9422/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/24/9422/ (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:15:y:2022:i:24:p:9422-:d:1001705

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 ().