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Article | Open Access

A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems

Jiaming Hu1, Boon-Han Lim2, Xiaoyun Tian1( ), Kang Wang1, Dachuan Xu1, Feng Zhang3, Yong 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
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Abstract

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 intelligenceneural networkssolar photovoltaic systemmeta-heuristic algorithm

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CAAI Artificial Intelligence Research
Volume 3,
2024
Article number: 9150031
DOI: 10.26599/AIR.2024.9150031
Cite this article:
Hu J, Lim B-H, Tian X, et al. A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems. CAAI Artificial Intelligence Research, 2024, 3: 9150031. https://doi.org/10.26599/AIR.2024.9150031
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Machine Learning and Optimization

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Received: 31 October 2023
Revised: 29 December 2023
Accepted: 19 January 2024
Published: 08 May 2024
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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