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Autonomous Intelligent Monitoring of Photovoltaic Systems: An In-depth Multidisciplinary Review
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  • Mohammadreza Aghaei,
  • Kolahi M.,
  • Amir Nedaei,
  • Venkatesh N.S.,
  • Sayyed Majid Esmailifar,
  • Amir Moradi Sizkouhi,
  • Aghamohammadi A.,
  • Aline Oliveira,
  • Aref Eskandari,
  • Parviz Parvin,
  • jafar milimonfared,
  • Sugumaran V.,
  • Ricardo Rüther
Mohammadreza Aghaei
Norges teknisk-naturvitenskapelige universitet - Alesund

Corresponding Author:[email protected]

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Kolahi M.
Amirkabir University of Technology Department of Aerospace Engineering
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Amir Nedaei
Amirkabir University of Technology Department of Electrical Engineering
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Venkatesh N.S.
Vellore Institute of Technology - Chennai Campus
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Sayyed Majid Esmailifar
Amirkabir University of Technology Department of Aerospace Engineering
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Amir Moradi Sizkouhi
Concordia University
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Aghamohammadi A.
Amirkabir University of Technology Department of Aerospace Engineering
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Aline Oliveira
Universidade Federal de Santa Catarina
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Aref Eskandari
Amirkabir University of Technology Department of Electrical Engineering
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Parviz Parvin
Amirkabir University of Technology Department of Energy Engineering and Physics
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jafar milimonfared
Amirkabir University of Technology Department of Electrical Engineering
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Sugumaran V.
Vellore Institute of Technology - Chennai Campus
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Ricardo Rüther
Universidade Federal de Santa Catarina
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Abstract

This study presents a comprehensive multidisciplinary review of autonomous monitoring and analysis of large-scale photovoltaic (PV) power plants using enabling technologies, namely artificial intelligence, machine learning, deep learning, internet of things, unmanned aerial vehicle, and big data analytics, aiming to automate the entire condition monitoring procedures of PV systems. Autonomous monitoring and analysis is a novel concept for integrating various techniques, devices, systems, and platforms to further enhance the accuracy of PV monitoring, thereby improving the performance, reliability, and service life of PV systems. This review article covers current trends, recent research paths and developments and future perspectives of autonomous monitoring and analysis for PV power plants. Additionally, this study identifies the main barriers and research routes for the autonomous and smart condition monitoring of PV systems, to address the current and future challenges of enabling the PV terawatt transition. The holistic review of the literature shows that the field of autonomous monitoring and analysis of PV plants is rapidly growing and is capable to significantly improve the efficiency and reliability of PV systems. It can also have significant benefits for PV plant operators and maintenance staff, such as reducing the downtime and the need for human operators in maintenance tasks, as well as increasing the generated energy.