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Integrating artificial intelligence (AI) into photovoltaic (PV) systems has become a revolutionary approach to improving the efficiency, reliability, and predictability of solar power generation. In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system. On the one hand, the integration with AI technology enables the optimization and improvement of the operational efficiency of PV systems. On the other hand, new challenges have been observed, mainly in the areas of data processing and model management. Moreover, advances in AI technology and hardware upgrades will lead to the rapid global popularization of new energy sources such as solar energy, which is expected to replace traditional energy sources. Finally, we describe forward-looking solutions including transfer learning, few-shot learning, and edge computing, as well as the state of the art.

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A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems

Show Author's information Jiaming Hu1Boon-Han Lim2Xiaoyun Tian1( )Kang Wang1Dachuan Xu1Feng Zhang3Yong Zhang4
Institute of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, China
Department of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang 43000, Malaysia
College of Mathematics and Information Science, Hebei University, Baoding 071002, China
Shenzhen Institutes of Advanced Technology of the Chinese Academy of Science, Shenzhen 518055, China


Integrating artificial intelligence (AI) into photovoltaic (PV) systems has become a revolutionary approach to improving the efficiency, reliability, and predictability of solar power generation. In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system. On the one hand, the integration with AI technology enables the optimization and improvement of the operational efficiency of PV systems. On the other hand, new challenges have been observed, mainly in the areas of data processing and model management. Moreover, advances in AI technology and hardware upgrades will lead to the rapid global popularization of new energy sources such as solar energy, which is expected to replace traditional energy sources. Finally, we describe forward-looking solutions including transfer learning, few-shot learning, and edge computing, as well as the state of the art.

Keywords: artificial intelligence, neural networks, solar photovoltaic system, meta-heuristic algorithm



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Publication history
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Publication history

Received: 31 October 2023
Revised: 29 December 2023
Accepted: 19 January 2024
Published: 08 May 2024
Issue date: December 2024


© The author(s) 2024.



The research was supported by the National Key R&D Program of China (No. 2022YFE0196100), and Fundamental Research Grant Scheme (FRGS) of Malaysia (FRGS/1/2022/TK0/UTAR/02/8). The above two grants are also parked under China-Malaysia Intergovernmental Science, Technology and Innovation Cooperative Programme 2023 (offer letter MOSTI.700-2/2/8(39), dated 9 February 2023).

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