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All Journal International Journal of Integrated Science and Technology
Domale Rutuja
Universitas HKBP Nomensen Pematang Siantar
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences

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Method for Monitoring and Identifying PV (Photovoltaic) System Failures Using Machine Learning Meenakshi A Thalor; Domale Rutuja
International Journal of Integrated Science and Technology Vol. 1 No. 5 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v1i5.686

Abstract

Artificial intelligence techniques have been utilized to address intricate practical challenges in various domains and are gaining popularity in the contemporary era. The principal aim of this article is to assess the prediction of power generation in three distinct photovoltaic configurations and the surveillance of measurement sensors, employing artificial intelligence and data extraction, to conform to the behavior of environmental factors in the examined region. Additionally, it encompasses the incorporation of the resulting models into the SCADA system using benchmarks, allowing the operator to actively monitor the power grid. Furthermore, it provides a method for real-time simulation and anticipation of photovoltaic systems and measurement detector within the framework of intelligent system.
Co-Authors Meenakshi A Thalor