Open Access

ARTICLE

Automatic PV Grid Fault Detection System with IoT and LabVIEW as Data Logger

Rohit Samkria¹, Mohammed Abd-Elnaby², Rajesh Singh³, Anita Gehlot³, Mamoon Rashid^4,*, Moustafa H. Aly⁵, Walid El-Shafai⁶

1 Project Engineer, NWTF, Indian Institute of Technology, Kanpur, India
2 Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, 21944, Saudi Arabia
3 School of Electronics and Electrical Engineering, Lovely Professional University, Jalandhar, India
4 School of Computer Science and Engineering, Lovely Professional University, Jalandhar, India
5 Department of Electronics and Communications Engineering, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport, Alexandria 1029, Egypt
6 Department Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

* Corresponding Author: Mamoon Rashid. Email:

(This article belongs to this Special Issue: Big Data Analytics and Artificial Intelligence Techniques for Complex Systems)

Computers, Materials & Continua 2021, 69(2), 1709-1723. https://doi.org/10.32604/cmc.2021.018525

Received 11 March 2021; Accepted 16 April 2021; Issue published 21 July 2021

Abstract

Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment, an automated monitoring system is developed. The automatic monitoring system assesses the voltage drop losses present in the DC side of the PV generator and generates a decimal weighted value depending on the defective solar panels and transmits this value to the remote station through an RF modem, and provides an indicator of the faulty solar panel over the built-in Interface LabVIEW. The managing of this GUI indicator helps the monitoring system to generate a panel alert for damaged panels in the PV system. Node MCU in the receiver section enables transmission of the fault status of PV arrays via Internet connectivity. The IoT-based Blynk app is employed for visualizing the fault status of the 3 × 3 PV array. The dashboard of Blynk visualizes every array with the status.

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Citations