Development of a Low-Cost Remote Fault Detection System for a Photovoltaic Power Plant

Kuei-Hsiang Chao (), Wen-Cheng Pu and Hsuan-Hao Chen
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Kuei-Hsiang Chao: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Wen-Cheng Pu: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Hsuan-Hao Chen: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Sustainability, 2022, vol. 14, issue 24, 1-24

Abstract: The main purpose of this study is to develop a cost-effective photovoltaic module array (PVMA) fault detection system. The system installs a fault detection module in the junction box at the back of each photovoltaic module (PVM), connects it to the Wi-Fi on the case site, and transfers data and information to the server for data analysis. The PVM outputs the voltage to the isolated DC-DC power module as the power supply of the overall circuits. The fault detection module sends data to the message queuing telemetry transport (MQTT) broker through the protocol in MQTT. As for the server host end, the visualization IoT development tool Node-RED is set up to display complex data sent by the fault detection module by means of data visualization. At the same time, it is linked to the open source time series database (OSTSDB) to process time series data. Finally, the results of the PVM are instantly sent to the maintenance personnel through an exception alert notification in order to inform the maintenance personnel to quickly rule out the failure. As the developed fault detection system hardware is more cost-effective than existing detection systems, the cost-effectiveness is favorable for mass production with market competitiveness.

Keywords: photovoltaic module array (PVMA); fault detection; node-red; open source time series database (OSTSDB); message queuing telemetry transport (MQTT) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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