Automatic Monitoring System for Online Module-Level Fault Detection in Grid-Tied Photovoltaic Plants

Belqasem Aljafari, Siva Rama Krishna Madeti, Priya Ranjan Satpathy, Sudhakar Babu Thanikanti () and Bamidele Victor Ayodele ()
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Belqasem Aljafari: Department of Electrical Engineering, College of Engineering, Najran University, Najran 11001, Saudi Arabia
Siva Rama Krishna Madeti: Department of Electrical and Electronics Engineering, SRKR Engineering College, Bhimavaram 534204, India
Priya Ranjan Satpathy: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India
Sudhakar Babu Thanikanti: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India
Bamidele Victor Ayodele: Department of Chemical Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia

Energies, 2022, vol. 15, issue 20, 1-28

Abstract: In this paper, a novel fault detection and diagnosis technique for a grid-tied photovoltaic (GTPV) with the ability of module-level fault location and differentiation is proposed. The proposed system measures the voltage, current, and temperature of the PV modules using low-cost sensors and critically compares them with the mathematical evaluated data to locate the type and location of the fault in the system. Additionally, a power line communication (PLC)-based low-cost PV monitoring system for tracking the operation of individual modules along with a fault detection algorithm is proposed to detect and locate the fault in the system. An intuitive online web application is also created to make it simple for users to view monitored data online. The suggested method is shown to have reduced computing needs; thus, the transmission of data and fault diagnosis is performed using the same microcontroller without the need for extra hardware or simulation software. The usefulness of the proposed method in identifying different fault occurrences in GTPV systems has been shown via experimental findings.

Keywords: solar photovoltaic; GTPV system; PLC; fault detection; MATLAB GUI (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
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