Cloud Computing and Machine Learning-based Electrical Fault Detection in the PV System-Reference-Cited by-同舟云学术

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Cloud Computing and Machine Learning-based Electrical Fault Detection in the PV System

Published:2023-05-28 Issue: Volume: Page:1-18
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Ragul S.¹,Tamilselvi S.²,Rengarajan S.²,Guna Sundari S.³

Affiliation:

1. Department of Electrical and Electronics Engineering, Chettinad College of Engineering and Technology, Karur, Tamil Nadu 639114, India

2. Department of Electrical and Electronics Engineering, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Tamil Nadu 603110, India

3. Department of Computer Science and Engineering, Velammal Engineering College, Chennai, Tamil Nadu 600066, India

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2023.2215214

Reference40 articles.

1. Review on Methods of Fault Diagnosis in Photovoltaic System Applications

2. An Intelligent Fault Detection Model for Fault Detection in Photovoltaic Systems

3. Environmental Impacts on the Performance of Solar Photovoltaic Systems

4. C.C. Hua, and P.K. Ku. “Implementation of a stand-alone photovoltaic lighting system with MPPT, battery charger and high brightness LEDs,” in Proceedings of the 2005 International Conference on Power Electronics and Drives Systems, Kuala Lumpur, Malaysia, 2005, pp. 1601–1605.

5. Review and Performance Evaluation of Photovoltaic Array Fault Detection and Diagnosis Techniques

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