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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Hee-Won Lim & Il-Kwon Kim & Ji-Hyeon Kim & U-Cheul Shin, 2022. "Simulation-Based Fault Detection Remote Monitoring System for Small-Scale Photovoltaic Systems," Energies, MDPI, vol. 15(24), pages 1-12, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9422-:d:1001705
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    References listed on IDEAS

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    1. Joshuva Arockia Dhanraj & Ali Mostafaeipour & Karthikeyan Velmurugan & Kuaanan Techato & Prem Kumar Chaurasiya & Jenoris Muthiya Solomon & Anitha Gopalan & Khamphe Phoungthong, 2021. "An Effective Evaluation on Fault Detection in Solar Panels," Energies, MDPI, vol. 14(22), pages 1-14, November.
    2. Aoyu Hu & Qian Sun & Hao Liu & Ning Zhou & Zhan’ao Tan & Honglu Zhu, 2019. "A Novel Photovoltaic Array Outlier Cleaning Algorithm Based on Sliding Standard Deviation Mutation," Energies, MDPI, vol. 12(22), pages 1-16, November.
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